데이터 전환 이전 전략
이 세분화의 범위는 CRM 위치에서 정보 이전 계획을 지정하는 것입니다. 진정으로 본질적으로 CRM은 유증기 시스템을 BSC CRM으로 전면 교체하는 것이 아니라 대신 빙 응용 프로그램 환경에서 클라이언트 상호 작용의 조정 및 방향을 제시합니다. 따라서 전통적 의미에서 큰 눈금 표 정보 이전은 필요하지 않으며 단지 소수의 정보 항목 만 BSC CRM으로 마이그레이션해야합니다.
데이터 이전은 일반적으로 '일회성'입니다. 라이브 이전에 활동. 자주 또는 임시 위주로 요구되는 진행중인 모든 정보는 인터페이스로 간주되며 정보 이전 범위의 일부가 아닙니다.
이 하위 절에서는 STEE-Infosoft가 CAMS 및 HPSM 유증 시스템에서 BSC CRM 시스템으로 정보를 마이그레이션하는 방법을 설명합니다.
STEE-InfoSoft는 CAMS 및 HPSM의 현재 유증기 데이터베이스를 마이그레이션하기위한 포괄적 인 정보 전환 및 마이그레이션 솔루션을 제공합니다. 이 솔루션은 입증 된 방법론 분석 및 전문 지식을 활용하여 데이터베이스 마이그레이션에 가장 적합하고 적합한 엔지니어링을 따릅니다. STEE-InfoSoft의 정보 마이그레이션 방법론 분석은 고객에게 결과의 품질, 일관성 및 진실성을 보장합니다.
표 11은 방법 론적 분석을 활용 한 STEE-InfoSoft 정보 마이그레이션 가치 제안을 보여줍니다.
표 11 : STEE-Infosoft 정보 마이그레이션 가치 제안.
세부 정보.
비용 효과적.
STEE-InfoSoft는 비용 효율적인 정보 마이그레이션 솔루션을 채택합니다. 정보 마이그레이션을 위해 최소한의 중단 시간을 달성 할 수 있습니다. 기계화 속도를 광범위하게 사용하여 작업을 향상시키고 실행 후 변경 및 보정을 실용적으로 만듭니다. 잘못 된 후행 및 수정 기능은 다년간 전환 재발생을 피하는 데 도움이됩니다. 사용자 정의를 통해 올바른 방식으로 직업을 획득 할 수 있습니다.
매우 짧은 가동 중지 시간.
대부분의 마이그레이션 절차는 실행중인 응용 프로그램 시스템의 외부에 있으며 정상적인 작업 흐름에 영향을주지 않으므로 가동 중지 시간이 최소화됩니다. 정보 전환이 단계적으로 수행되도록하여 가동 중지 시간을 줄입니다.
데이터 무결성 보증.
스크립트 및 계획은 정보를 테스트하고 형식화 할 때 이후 사용을 위해 자동으로 생성됩니다.
마이그레이션 프로세스 제어.
빙 시스템의 다운 타임을 줄이기 위해 주입 및 부담 절차를 실행하기위한 ETL (Extract, Transform 및 Load) 스크립트 만 작성합니다. Fieldss 통합, 정보 필터링, 정보 분할, 필드 정의 변경 및 필드 내용 해석. 추가, 삭제, 변환 및 집계, 정보 정리에 대한 유효성 검사 규정.
1.1. 데이터 마이그레이션 개요.
데이터 마이그레이션은 한 위치, 저장 매체 또는 하드웨어 / 소프트웨어 시스템에서 다른 위치로 정보를 전송하는 것입니다. 이주 시도는 종종 능숙한 하부 구조 또는 관심사 요구의 변경에서 상승에 대한 요구에 의해 촉발된다.
정보 마이그레이션에서 가장 좋은 패턴은 성공적인 정보 마이그레이션을 위해 내장 된 두 가지 규칙을 권장합니다.
새로운 (마크) 정보 샵을 설치하는 유일한 목적에 전념하는 사업으로 정보 마이그레이션을 수행하십시오. 데이터 마이그레이션 계획, 데이터 마이그레이션 분석 및 설계, 데이터 마이그레이션 구현, 데이터 마이그레이션 폐쇄 등 네 가지 주요 단계에서 정보 마이그레이션을 수행합니다 (1.1 참조).
애드온에서 성공한 정보 마이그레이션 사업은 기회를 최대화하고 위험을 완화하는 1 초입니다. 아래의 중요한 성공 요인이 확인되었습니다.
정보 마이그레이션을 독립적 인 사업으로 수행하십시오.
절차 전반에 걸쳐 전망을 수립하고 관리하십시오.
현재와 미래의 정보와 관심사에 대한 이해.
전문 지식을 가진 사람을 유증 정보를 부르는 사람으로 식별하십시오.
유증 증서를 사용할 수있는 인증서를 수집하십시오.
역할을 수행하는 정보 이전 정의 & # 038; A; 의무.
정보 내용, 품질 및 구성에 대한 포괄적 인 개요를 수행하십시오.
관심사 정보 및 정보 품질의 중요성을 파악하기 위해 관심 소유자 및 이해 관계자와 협력하십시오.
1.2. STEE-Info 데이터 마이그레이션 프로젝트 수명주기.
표 12는 STEE-Info 데이터 마이그레이션 프로젝트 수명주기의 각 단계에 대한 상위 단계 절차를 나열합니다.
모든 정보 마이그레이션 작업이 데이터 마이그레이션 프로젝트 수명주기의 네 단계를 따르지만 상위 및 하위 절차는 각 마이그레이션 프로젝트의 크기, 범위 및 복잡성에 따라 달라질 수 있습니다. 따라서 아래 정보는 정보 마이그레이션 시도를 개발, 측정 및 구현하기위한 가이드 라인. 각 상위 및 하위 절차는 Datas Migration Plan에 포함되어야합니다. 적절한 것으로 간주되지 않는 절차의 경우 제외에 대한 정당성을 Datas Migration Plan에 문서화해야합니다.
도표 12 : 확인 된 고위 기업을 가진 자료 이동 프로젝트 수명주기.
데이터 마이그레이션 계획 단계.
데이터 마이그레이션 분석 & # 038; A; 디자인 단계.
데이터 마이그레이션 구현 단계.
데이터 마이그레이션 종료 단계.
계획 데이터 마이그레이션 프로젝트.
평가 결과 분석.
문서 데이터 마이그레이션 결과.
데이터 마이그레이션 요구 사항 결정.
보안 컨트롤 정의.
문서화 된 교훈.
현재 환경 평가.
디자인 데이터 환경.
지식 이전을 수행하십시오.
데이터 마이그레이션 계획 개발.
마이그레이션 절차 설계.
변환 데이터 변환 (필요에 따라)
데이터 마이그레이션 결과를 전달합니다.
팀 역할 및 직무 정의 및 할당.
데이터 품질 검증.
데이터 마이그레이션 (평가판 / 배포)
마이그레이션 결과 검증 (반복)
마이그레이션 후 결과의 유효성 확인.
정보 이전 사업의 라이프 사이클 동안, 분대는 1.2에 나와있는 활동을 통해 정보를 이동시킵니다.
팀은 새로운 마크 정보 상점에 성공적인 정보 부담을 보장하기 위해 필요에 따라 이러한 정보 방향 활동을 반복합니다.
1.3. 데이터 마이그레이션 지침.
1.3.1. 데이터 마이그레이션 접근법.
1.3.1.1. 마스터 데이터 & # 8211; (예 : 고객, 자산)
공격은 마에스트로 정보가 CRM으로 마이그레이션되어 이러한 조건을 제공한다는 것입니다.
정보가있는 응용 프로그램이 CRM으로 대체됩니다.
마에스트로 레코드는 사후에 CRM 기능을 백업하는 데 필요합니다.
기 본적 인 운영, 적용 범위 또는 법적 / 법정 요구가 있습니다.
마에스트로 정보가 최신 정보입니다 (누락 된 것으로 표시된 레코드는 이전 할 필요가 없음) 또는 다른 이전을 백업해야합니다.
유증 정보는 일상적인 CRM 시스템 실행에 악영향을 미치지 않는 정도의 충분한 품질을 지니고 있거나 비즈니스 요구 사항에 부합하도록 정보 마이그레이션 절차에서 충분히 개선 / 개선 될 것입니다.
참고 : CRM으로 대체되지 않고 특정 기능을 백업하기 위해 CRM에서 필요로하는 응용 프로그램에 마에스트로 정보가있는 경우 정보는 마이그레이션되지 않고 동적 쿼리 조회를 사용하여 CRM에서 액세스됩니다. 동적 질문 조회는 처음 신청서에 정보가 필요할 때 언제든지 정보에 액세스하는 실시간 질문입니다. 이 공격의 장점은 다음과 같습니다.
시스템 환경 전체에서 정보의 중복을 피하십시오.
구식 CRM의 정보를 피하십시오.
자주 사용되는 인터페이스의 개발 및 실행을 피하여 CRM 내의 정보를 업데이트합니다.
CRM 시스템 내의 정보 측정을 줄입니다.
1.3.1.2. '열기 & # 8216; 거래 정보 (예 : 서비스 티켓)
공격은 '열린 상태 (open & # 8216; 트랜잭션 정보는 다음 조건이 모두 충족되지 않으면 CRM로 마이그레이션되지 않습니다.
기 본적 인 운영, 적용 범위 또는 법적 / 법정 요구가 있습니다.
유증 제도는 BSC CRM이 시간의 흐름에 따라 착수하여 결과적으로 폐기되어야한다. unfastened 포인트.
병렬 '실행 중지' 유증 제도 내의 풀리지 않은 부분은 운영상, 타이밍 상 또는 자원상의 제한으로 인해 비실용적이다.
CRM 체격과 구조는 CRM 생성 포인트를 통해 유증 시스템 포인트를 정확하고 일관되게 읽을 수 있습니다.
우려 경영자는 여러 사업 단계에 걸쳐 적절한시기에 정교한 수준으로 정보를 제공하고 사인 오프하는 자원을 저지 할 수 있습니다.
1.3.1.3. 역사적인 마에스트로 및 거래 정보.
이러한 모든 조건이 충족되지 않으면 과거 정보가 마이그레이션되지 않습니다.
체류하는 시스템을 활용함으로써 충족시킬 수없는 기본적인 운영, 적용 범위 또는 법적 / 법적 요구가 있습니다.
유증 제도는 BSC CRM 업무 시간표에서 BSC CRM 사업의 직접적인 결과로 폐기되어야합니다.
아카이빙 솔루션은 요구 사항을 충족시킬 수 없습니다.
CRM 체격과 구조는 CRM 생성 포인트를 통해 유증 시스템 포인트를 정확하고 일관되게 읽을 수 있습니다.
우려 경영자는 여러 사업 단계에 걸쳐 적절한시기에 정교한 수준으로 정보를 제공하고 사인 오프하는 자원을 저지 할 수 있습니다.
1.3.2. 데이터 마이그레이션 테스트주기.
마이그레이션 절차를 증명하고 확인하기 위해 미기의 최종 결론이되기 전에 세 가지 증명 리듬이 존재할 것을 제안합니다.
Trial Load 1 : 주입 및 부담 방식의 측정 테스트 단위.
시험로드 2 : 각 정보 엔터티에 대한 완벽한 종단 간 정보 마이그레이션 절차의 첫 번째 시도. 이러한 부담의 주된 의도는 추출물 방식의 작업을 올바르게 보장하고, 제시하는 국가의 변환이 옳으며, 짐작할 수있는 방식으로 정보를 CRM에 성공적으로 제공 할 수 있도록하는 것입니다. 분류되지 않은 정보 엔티티는 필요에 따라 기록되지 않은 컷오버 중에 수행되는 것과 동일한 순서로로드됩니다.
Trial Cutover : 미기록 정보 이전 절차를 완전히 마쳤습니다. 실행은 컷오버 프로그램을 활용하여 프로그램이 합리적이고 가능한 시간 내에 완료 될 수 있음을 공식화합니다. 결론적 인 정리 작업 세트는 테스트 컷 오버에서 비롯됩니다 (정보 품질 문제로 인해 마이그레이션 중에 실패한 레코드의 경우). 테스트 컷오버가 적어도 하나는있을 것입니다. 복잡하고 나쁜 마이그레이션의 경우 결과가 완전히 만족스럽고 100 % 정확할 때까지 여러 번의 테스트를 수행 할 수 있습니다.
라이브 컷 오버 (Live Cutover) : BSC CRM을 특별한 릴리스의 라이브로 수정하는 데 필요한 모든 약속을 실행합니다. 이러한 사업의 대부분은 정보 이전과 관련이 있습니다.
1.3.3. 데이터 클렌징.
정보가 성공적으로 마이그레이션되기 전에 데이터 정리가 필요하기 때문에 정보 정리는 모든 정보 마이그레이션 활동의 가져 오기 구성 요소입니다.
CRM으로 성공적으로 마이그레이션 할 수 있도록 일관되고 표준화되고 올바른 형식으로 데이터가 요구됩니다 (예 : CRM은 구조화 된 참조로 참조를 보유하지만 일부 유증 시스템은이 정보를 자유 형식으로 유지할 수 있음)
마이그레이션이 완료되면 CRM에서 필수적인 모든 Fieldss가 채워지도록 데이터 요구가 완료되어야합니다. 상원 의원으로 지정된 모든 Fieldss는 깨끗하게 남겨 두어 방치하는 일을 게을리 할 것입니다.
데이터는 중복 제거되어야하며 정의 된 관심 사항 절차를 효율적이고 올바르게 지원할 수 있도록 충분한 품질이어야합니다. 중복 된 레코드는 시작시 누락으로 표시하거나 (선호 옵션) 추출 / 변환 프로세스에서 제외해야합니다.
레거시 정보 Fieldss는 오용되었을 수 있습니다 (이 필드는이 필드가 처음 사용 된 것과 다른 정보를 유지합니다). 데이터 정리는 이러한 문제를 해결해야하며이 정보가 제외되어야하는지 (즉, 마이그레이션되지 않았는지) 또는 더 적절한 분야로 이전되어야하는지 여부를 결정해야합니다.
BSC CRM으로 이전하기 위해 STEE-Info에 제공된 정보를 보증하는 것은 정보 소유주 (즉, MOM)의 의무입니다 (유증 유무에 상관없이 또는 BSC CRM을 위해 특별히 작성된 템플렛에서든).
데이터 정리는 가능한 한 다음과 같은 이유로 처음 시작할 때, 즉 유증 시스템에서 수행되어야합니다.
정보 변경 동결이 지형 학적 관점에 놓여 있지 않는 한, 추출 된 데이터 세트는 초창기 시스템에서 지형 학적 포인트를 취하는 업데이트로 인해 추출 된대로 곧 매월 매월 비게됩니다. 가장 최근의 업데이트를 얻기 위해 매월 중순에 정보를 다시 추출하면 정보 정리 작업이 덮어 쓰기됩니다. 따라서 클리닝은 각 클립에서 새로운 데이터 세트가 추출되도록 반복됩니다. 대부분의 경우 이것은 비실용적이며 큰 시도가 필요합니다.
데이터 청산은 일반적으로 우려 활동입니다. 따라서 기존 유증 제도를 정화하는 것은 사람들이 이미 유증 시스템에 참여하고 있다는 점과 응용 프로그램에 익숙하다는 장점이 있습니다. 정보가 제시 영역에 저장 될 때 인스턴스가 아닌 것. 특정 경우에 정보의 실수로 인한 위험이 추가 되더라도 특정 등급의 기계 제어 세척을 개발하는 것이 가능할 수 있습니다.
정보 클리닝이 처음에 완료되면, 각 클립에 새로운 (즉, 보다 최근의) 주입이 취해지며, 최신 클리닝 동작의 결과는 여분의 시도없이 주입에서 자동으로 발견 될 것이다.
1.3.4. 사전 마이그레이션 테스트.
두 가지 핵심 국가에 대한 중단 테스트 : 논리적 인 실수와 실제적인 실수. 물리적 실수는 일반적으로 본질적으로 구문 론적이며 쉽게 식별하고 해결할 수 있습니다. 물리적 인 실수는 함수 시도의 품질을 높이기 위해 필요하지 않습니다. 오히려, 이 정도의 증명은 변환 실험에서 사용 된 스크립팅 언어 통신의 의미론을 다루고 있습니다. 테스트는 논리적 실수를 결정하고 결정하는 곳입니다. 첫 번째 조치는 기능을 중지시키는 것입니다. 기능이 성공적으로 완료 되더라도 다음과 같은 문의는 계속해야합니다.
이 책을 몇 권이나 만들었습니까?
정확한 기록이 만들어 졌습니까?
정보가 올바른 Fieldss에로드 되었습니까?
정보의 형식이 맞습니까?
실제로 매핑되는 정보는 새로운 정보 구조와 물리적으로 상호 작용할 때까지 대부분의 사람들에게 의미가 없습니다. 자주, 이것은 대량의 핵 변환과 기능 요구가 발견되는 곳이다. 대부분의 사람들은 더 이상 그 장소에 없을 때까지 뭔가를 놓친 것을 인식하지 못합니다. 이 지상을 위해, 가능한 한 조금씩 채워진 마크 정보 구조에 그들을 풀어 놓는 것이 중요합니다. 정보 마이그레이션 증명 단계는 가능한 빨리 핵 문제의 설계 및 구성 단계 이전에 발생하는 것을 보장하기 위해 가능한 한 모든 비트에 도달해야합니다. 그렇지 않으면 몇 개월의 개발 시도가 추가 마이그레이션 요구가 쉽지만 정보 이론 계정에 쉽게 손상 될 수 있으므로 잃어 버릴 수 있습니다. 이것은 구부러진 상태에서 정보 이론 계정에 기반한 응용 프로그램을 크게 변경해야합니다.
1.3.5. 마이그레이션 유효성 검사.
이전이 성공으로 간주되기 전에, 한 가지 중요한 조치가 남아 있습니다. 즉, 마이그레이션 후 환경을 공식화하고 모든 전망을 저지하기 위해 전방위에 도달했는지 확인하는 것입니다. 하한선에서 웹 프로 그램, 파일 사용 권한, 디렉토리 구성 및 데이터베이스 / 응용 프로그램을 검증해야합니다. 이는 비 프로덕션 테스팅을 통해 자주 수행됩니다. 패키지 마이그레이션을 공식화하는 또 다른 좋은 방법은 문제가 미리 매핑 된 방식을 벤치마킹하는 것입니다. 마이그레이션을 수행 한 후 해당 벤치 마크와 마이그레이션 후의 동작을 비교하십시오. 벤치 마크 측정을 롤업하는 가장 효과적인 방법은 다양한 비즈니스 영역 및 해당 개인 비즈니스에 대한 품질 측정 지표를 롤업 및 분석하는 것입니다.
1.3.6. 데이터 변환 프로세스.
이 기간 동안 매핑 된 정보 및 정보 전환 계획이 사용됩니다. 이 절차의 소요 기간 및 기간은 다음 사항에 따라 결정됩니다.
마이그레이션 할 정보의 합계입니다.
마이그레이션 할 유증 시스템의 수.
웨이터 공개 프리젠 테이션과 같은 리소스 제한.
이 절차에 의해 대량 생산 된 실수.
전이 실수 방향 공격은 과도기 공격이 가능한 한 잠시 동안 심각한 실수를 포함하는 모든 기록을 거부하는 것을 목표로합니다. 전환 설치 중에 수정 설치가 제공됩니다. 가능하다면 빙 수정안 인터페이스를 활용할 것입니다.
실수는 다음과 같이 분류 할 수 있습니다.
치명적인 실수 & # 8211; 이는 데이터베이스에 히스토리가로드되는 것을 막을 정도로 심각합니다. 여기에는 데이터베이스 통합을 위반하는 실수가 포함됩니다. 중복 된 기본 키 또는 유효하지 않은 외부 추기경과 같은. 이러한 실수는 전환 전과 도중에 정보를 정리하는 중점이 될 것입니다. 사용자 상호 작용없이 실수를 바로 잡기위한 시도는 일반적으로 효과가 없습니다.
치명적이지 않은 실수 & # 8211; 덜 심각한 것입니다. 영향을받은 실수를 데이터베이스에로드하고 실수를 통합하면 실수가 레코드에 첨부 된 작업 방향 포인트를 통해 사용자에게 전달됩니다. 실수는 사용자의 정보로 수정 될 것입니다.
자동 수정 된 실수 & # 8211; 위반 정보 포인트는 이전 능력에 의해 선행 적으로 합의 된 가치로 대체된다. 이 작업은 사용자와 함께 전환 절차가 시작되기 전에 업데이트해야하는 값을 찾기 위해 수행됩니다.
정보 전환 절차에서 수입 업체 중 하나는 데이터 증명입니다. 광범위한 의미의 데이터 증명은 Se 단위의 인터링스 (interlongual) 연주 절차를 검사하거나 전환 절차가 정보 계속 기능인지 어느 정도인지 정보를 조사하는 것을 포함합니다.
사용되는 일반적인 확인 방법은 다음과 같습니다.
재정적 인 확인 (기본 회계 값에 대한 전환 전 사전 확인, 일반 총액에 대한 종속 확인) & # 8211; 역사, 감사, 적합성의 면전에서 중앙 집중적으로 수행되어야한다. A; 위험 방향;
의무적 인 제외 확인 및 수정 (생산 작업을 피하기 위해 해결해야하는 제외 항목) & # 8211; 웹 방향, 감사, 적합성의 면전에서 다시 한 번, 정정을 뒷받침하고 사망에 이르기 위해 중앙에서 검토 할 수 있습니다. A; 위험 방향;
상세한 확인 (내부 정보가 모두 인쇄되고 사용자가 유증기 정보로 무작정 정교한 확인을해야하는 경우) & # 8211; 세분 배치 및 세분 소장에 의한 검증 승인을 마친 후 세분에서 수행되어야한다. 과.
미리 정의 된 파일을 사용하여 전자 파일을 작성 (현장별 또는 레코드 별).
1.4. 데이터 마이그레이션 방법.
유증 시스템에서 정보를 Siebel CRM으로 재 할당하는 주요 방법은 Siebel Enterprise Integration Manager (EIM)를 사용하는 것입니다. 이 설치로 비 Siebel 데이터베이스와 Siebel 데이터베이스간에 정보를 양방향으로 교환 할 수 있습니다. Siebel 데이터베이스와 다른 회사 정보 시작 부분 사이에 정보를 전송하는 Siebel eAI 구성 그룹의 서버 구성 요소입니다. 이러한 정보의 교환은 EIM의 표를 사용하는 중대장단이라는 중개자를 통해 이루어집니다. EIM 테이블 형식은 Siebel 응용 프로그램 데이터베이스와 기타 정보 소스 사이에 제시되는 국가 역할을합니다.
아래 그림은 HPSM, CAMS 및 IA 데이터베이스의 정보를 Siebel CRM 데이터베이스로 마이그레이션하는 방법을 보여줍니다.
1.5. 데이터 변환 및 마이그레이션 일정.
다음은 HPMS 및 CAMS 및 IA 데이터베이스를 Siebel CRM 데이터베이스로 마이그레이션하기위한 정보 변환 및 마이그레이션 계획입니다.
1.6. 위험 및 구내.
1.6.1. 위험.
MOM은 대용량 및 / 또는 복잡한 정보 집합을 자신있게 수용 할 수 없습니다. 정보 마이그레이션이 3 배 (시스템 시험, 테스트 컷 오버 및 기록되지 않은 컷오버)의 하한을 조정해야하기 때문에 마이그레이션 된 정보 집합을 종합적으로 증명하는 데 필요한 시도가 중요합니다. 추가 기능에서 컷 오버시 능숙한 정보는 제한된 클립 창을 야간이나 주말과 같은 제한된 클립 작업에 사용할 수 있습니다. MOM은 BSC CRM 시간 척도에 따라 유증 정보를 종합적으로 정리할 수 없습니다. BSC CRM 으로의 이전은 유증 시스템에서 수행되는 정화 활동에 의존 할 수 있기 때문에이를 달성하기위한 우려 내에서 요구되는 시도는 마이그레이션되는 정보의 양에 비례하여 증가 할 것입니다. 필요한 시간 척도로이 운동을 끝내지 않으면 계획된 컷오프를위한 클립에서 정보가 BSC CRM으로 마이그레이션 될 수 없습니다. 화해가 필요한 기준에 도달하지 못하면 녹음되지 않은 시스템의 정보 실수 량이 증가 할 수 있습니다. 편이성이 커지면 변칙이 발생할 가능성이 커집니다. 이 중 일부는 발견되지 않을 수도 있습니다. 가장 좋은 경우에는 이러한 정보 문제가 염려되고 실수를 바로 잡는 데 드는 운영비를 부담 할 수 있습니다 이벤트 후. 최악의 경우 이것은 부정확 한 정보에 대한 우려로 이어질 수 있습니다. BSC CRM으로 마이그레이션 된 정보가 많을수록 컷오버는 더욱 복잡해지고 시간이 지나면 마이그레이션 작업을 완료하지 못하는 위험도가 높아집니다. 더 많은 리소스 또는 능숙한 제한이이 위험 요소에 추가 될 수 있습니다. 착수 규모 때문에 정보 이동은 초기 시스템 체격, 기능 테스트 및 사용자 신빙성 테스트와 같은 추기 활동과 관련하여 착수 및 우려를 벗어날 수 있습니다.
1.6.2. 가옥.
데이터 액세스 & # 8211; CAMS, HPSM 및 IA 응용 프로그램 내에서 보유 된 정보에 대한 정보는 정보 프로파일 링, 정보 시작 지정 및 기능적 및 능숙한 사양 작성을 가능하게해야합니다. 정보 마이그레이션 책을 실행하려면 HPMS, CAMS 및 IA 데이터베이스에 대한 액세스 연결이 필요합니다. MOM은 HPMS 및 CAMS 및 IA 데이터베이스의 정보 마이그레이션을 위해 ETL 서적을 실행하기위한 워크 스테이션을 제공합니다. 정보 이전 단계에서 유증기 HPMS 및 CAMS 및 IA 데이터베이스에 대한 스키마 변경이 없어야합니다. MOM은 개발 된 ETL 도서를 증명하기위한 생산 정보 샘플을 제공합니다. MOM은 자원 편리성에 관심이 있습니다.
정보 프로파일 링, 정보 시작 지정 및 기능적 및 능숙한 사양 작성을 돕는 데 필요합니다.
CAMS & # 038;에서 정보 주입을 개발하고 실행하는 데 필요합니다. A; HPSM 시스템.
정보 톤의 유효성을 확인 / 조정 / 로그 오프해야합니다.
정보 클렌징에 필요합니다.
시작 정보의 데이터 정리는 MOM. A의 의무입니다. STEE-Info는 정보 이전 절차 중에 정보의 변칙적 인 부분을 돕습니다. 그럼에도 불구하고 STEE-Info는 CAMS & # 038; A; HPSM 응용 프로그램. 정보 품질에 따라 정보 정리는 상당한 시도가 필요하며 많은 자원에 영향을 미칩니다. 정보 이동 요구 사항의 범위는 아직 결정되지 않았습니다. 정보 개체가 식별되면 정보 개체 레지스트리에 추가됩니다.
관련 게시물:
최근 게시물.
14 장 : 감염의 확산 & # 8211; 질병 전송 / 접촉 전달, 차량 전송, 벡터 전송.
Multivariable Calculus 제 17 장 : 벡터 미적분 정의.
데이터 전환 이전 전략
이 세분화의 범위는 CRM 위치에서 정보 이전 계획을 지정하는 것입니다. 진정으로 본질적으로 CRM은 유증기 시스템을 BSC CRM으로 전면 교체하는 것이 아니라 대신 빙 응용 프로그램 환경에서 클라이언트 상호 작용의 조정 및 방향을 제시합니다. 따라서 전통적 의미에서 큰 눈금 표 정보 이전은 필요하지 않으며 단지 소수의 정보 항목 만 BSC CRM으로 마이그레이션해야합니다.
데이터 이전은 일반적으로 '일회성'입니다. 라이브 이전에 활동. 자주 또는 임시 위주로 요구되는 진행중인 모든 정보는 인터페이스로 간주되며 정보 이전 범위의 일부가 아닙니다.
이 하위 절에서는 STEE-Infosoft가 CAMS 및 HPSM 유증 시스템에서 BSC CRM 시스템으로 정보를 마이그레이션하는 방법을 설명합니다.
STEE-InfoSoft는 CAMS 및 HPSM의 현재 유증기 데이터베이스를 마이그레이션하기위한 포괄적 인 정보 전환 및 마이그레이션 솔루션을 제공합니다. 이 솔루션은 입증 된 방법론 분석 및 전문 지식을 활용하여 데이터베이스 마이그레이션에 가장 적합하고 적합한 엔지니어링을 따릅니다. STEE-InfoSoft의 정보 마이그레이션 방법론 분석은 고객에게 결과의 품질, 일관성 및 진실성을 보장합니다.
표 11은 방법 론적 분석을 활용 한 STEE-InfoSoft 정보 마이그레이션 가치 제안을 보여줍니다.
표 11 : STEE-Infosoft 정보 마이그레이션 가치 제안.
세부 정보.
비용 효과적.
STEE-InfoSoft는 비용 효율적인 정보 마이그레이션 솔루션을 채택합니다. 정보 마이그레이션을 위해 최소한의 중단 시간을 달성 할 수 있습니다. 기계화 속도를 광범위하게 사용하여 작업을 향상시키고 실행 후 변경 및 보정을 실용적으로 만듭니다. 잘못 된 후행 및 수정 기능은 다년간 전환 재발생을 피하는 데 도움이됩니다. 사용자 정의를 통해 올바른 방식으로 직업을 획득 할 수 있습니다.
매우 짧은 가동 중지 시간.
대부분의 마이그레이션 절차는 실행중인 응용 프로그램 시스템의 외부에 있으며 정상적인 작업 흐름에 영향을주지 않으므로 가동 중지 시간이 최소화됩니다. 정보 전환이 단계적으로 수행되도록하여 가동 중지 시간을 줄입니다.
데이터 무결성 보증.
스크립트 및 계획은 정보를 테스트하고 형식화 할 때 이후 사용을 위해 자동으로 생성됩니다.
마이그레이션 프로세스 제어.
빙 시스템의 다운 타임을 줄이기 위해 주입 및 부담 절차를 실행하기위한 ETL (Extract, Transform 및 Load) 스크립트 만 작성합니다. Fieldss 통합, 정보 필터링, 정보 분할, 필드 정의 변경 및 필드 내용 해석 추가, 삭제, 변환 및 집계, 정보 정리에 대한 유효성 검사 규정.
1.1. 데이터 마이그레이션 개요.
데이터 마이그레이션은 한 위치, 저장 매체 또는 하드웨어 / 소프트웨어 시스템에서 다른 위치로 정보를 전송하는 것입니다. 이주 시도는 종종 능숙한 하부 구조 또는 관심사 요구의 변경에서 상승에 대한 요구에 의해 촉발된다.
정보 마이그레이션에서 가장 좋은 패턴은 성공적인 정보 마이그레이션을 위해 내장 된 두 가지 규칙을 권장합니다.
새로운 (마크) 정보 샵을 설치하는 유일한 목적에 전념하는 사업으로 정보 마이그레이션을 수행하십시오. 데이터 마이그레이션 계획, 데이터 마이그레이션 분석 및 설계, 데이터 마이그레이션 구현, 데이터 마이그레이션 폐쇄 등 네 가지 주요 단계에서 정보 마이그레이션을 수행합니다 (1.1 참조).
애드온에서 성공한 정보 마이그레이션 사업은 기회를 최대화하고 위험을 완화하는 1 초입니다. 아래의 중요한 성공 요인이 확인되었습니다.
정보 마이그레이션을 독립적 인 사업으로 수행하십시오.
절차 전반에 걸쳐 전망을 수립하고 관리하십시오.
현재와 미래의 정보와 관심사에 대한 이해.
전문 지식을 가진 사람을 유증 정보를 부르는 사람으로 식별하십시오.
유증 증서를 사용할 수있는 인증서를 수집하십시오.
역할을 수행하는 정보 이전 정의 & # 038; A; 의무.
정보 내용, 품질 및 구성에 대한 포괄적 인 개요를 수행하십시오.
관심사 정보 및 정보 품질의 중요성을 파악하기 위해 관심 소유자 및 이해 관계자와 협력하십시오.
1.2. STEE-Info 데이터 마이그레이션 프로젝트 수명주기.
표 12는 STEE-Info 데이터 마이그레이션 프로젝트 수명주기의 각 단계에 대한 상위 단계 절차를 나열합니다.
모든 정보 마이그레이션 작업이 데이터 마이그레이션 프로젝트 수명주기의 네 단계를 따르지만 상위 및 하위 절차는 각 마이그레이션 프로젝트의 크기, 범위 및 복잡성에 따라 달라질 수 있습니다. 따라서 아래 정보는 정보 마이그레이션 시도를 개발, 측정 및 구현하기위한 가이드 라인. 각 상위 및 하위 절차는 Datas Migration Plan에 포함되어야합니다. 적절한 것으로 간주되지 않는 절차의 경우 제외에 대한 정당성을 Datas Migration Plan에 문서화해야합니다.
도표 12 : 확인 된 고위 기업을 가진 자료 이동 프로젝트 수명주기.
데이터 마이그레이션 계획 단계.
데이터 마이그레이션 분석 & # 038; A; 디자인 단계.
데이터 마이그레이션 구현 단계.
데이터 마이그레이션 종료 단계.
계획 데이터 마이그레이션 프로젝트.
평가 결과 분석.
문서 데이터 마이그레이션 결과.
데이터 마이그레이션 요구 사항 결정.
보안 컨트롤 정의.
문서화 된 교훈.
현재 환경 평가.
디자인 데이터 환경.
지식 이전을 수행하십시오.
데이터 마이그레이션 계획 개발.
마이그레이션 절차 설계.
변환 데이터 변환 (필요에 따라)
데이터 마이그레이션 결과를 전달합니다.
팀 역할 및 직무 정의 및 할당.
데이터 품질 검증.
데이터 마이그레이션 (평가판 / 배포)
마이그레이션 결과 검증 (반복)
마이그레이션 후 결과의 유효성 확인.
정보 이전 사업의 라이프 사이클 동안, 분대는 1.2에 나와있는 활동을 통해 정보를 이동시킵니다.
팀은 새로운 마크 정보 상점에 성공적인 정보 부담을 보장하기 위해 필요에 따라 이러한 정보 방향 활동을 반복합니다.
1.3. 데이터 마이그레이션 지침.
1.3.1. 데이터 마이그레이션 접근법.
1.3.1.1. 마스터 데이터 & # 8211; (예 : 고객, 자산)
공격은 마에스트로 정보가 CRM으로 마이그레이션되어 이러한 조건을 제공한다는 것입니다.
정보가있는 응용 프로그램이 CRM으로 대체됩니다.
마에스트로 레코드는 사후에 CRM 기능을 백업하는 데 필요합니다.
기 본적 인 운영, 적용 범위 또는 법적 / 법정 요구가 있습니다.
마에스트로 정보가 최신 정보입니다 (누락 된 것으로 표시된 레코드는 이전 할 필요가 없음) 또는 다른 이전을 백업해야합니다.
유증 정보는 일상적인 CRM 시스템 실행에 악영향을 미치지 않는 정도의 충분한 품질을 지니고 있거나 비즈니스 요구 사항에 부합하도록 정보 마이그레이션 절차에서 충분히 개선 / 개선 될 것입니다.
Note: Where the maestro informations resides in an application that is non being replaced by CRM, but is required by CRM to back up specific functionality, the informations will NOT be migrated but accessed from CRM utilizing a dynamic query look-up. A dynamic question look-up is a real-time question accessing the information in the beginning application as and when it is required. A The advantages of this attack are ;
Avoids the duplicate of informations throughout the system landscape.
Avoids informations within CRM going out-of-date.
Avoids the development and running of frequent interfaces to update the informations within CRM.
Reduces the measure of informations within the CRM systems.
1.3.1.2. ‘Open ‘ Transactional informations ( e. g. Service Tickets )
The attack is that ‘open ‘ transactional informations will NOT be migrated to CRM unless ALL these conditions are met:
There is a cardinal operational, coverage or legal/statutory demand.
The bequest system is to be decommissioned as a consequence of the BSC CRM undertaking in timescales that would forestall a ‘run down ‘ of unfastened points.
The parallel ‘run down ‘ of unfastened points within the bequest system is impractical due to operational, timing or resource restraints.
The CRM physique and structures permit a correct and consistent reading of bequest system points aboard CRM-generated points.
The concern proprietor is able to perpetrate resources to have informations rapprochement and sign-off at a elaborate degree in a timely mode across multiple undertaking stages.
1.3.1.3. Historical Maestro and Transactional informations.
The attack is that historical informations will non be migrated unless ALL these conditions are met:
There is a cardinal operational, coverage or legal/statutory demand that can non be met by utilizing the staying system.
The bequest system is to be decommissioned as a direct consequence of the BSC CRM undertaking within the BSC CRM undertaking timeline.
An archiving solution could non run into demands.
The CRM physique and structures permit a correct and consistent reading of bequest system points aboard CRM-generated points.
The concern proprietor is able to perpetrate resources to have informations rapprochement and sign-off at a elaborate degree in a timely mode across multiple undertaking stages.
1.3.2. Data Migration Testing Cycles.
In order to prove and verify the migration procedure it is proposed that there will be three proving rhythms before the concluding unrecorded burden:
Trial Load 1: Unit of measurement testing of the infusion and burden modus operandis.
Trial Load 2: The first trial of the complete end-to-end informations migration procedure for each information entity. The chief intent of this burden is to guarantee the extract modus operandis work right, the presenting country transmutation is right, and the burden modus operandis can lade the information successfully into CRM. The assorted information entities will non needfully be loaded in the same sequence as will be done during the unrecorded cutover.
Trial Cutover: a complete dry run of the unrecorded informations migration procedure. The executing will be done utilizing the cutover program in order to formalize that the program is sensible and possible to finish in the in agreement timescale. A concluding set of cleansing actions will come out of test cutover ( for any records which failed during the migration because of informations quality issues ) . There will be at least one test cutover. For complex, bad, migrations several test tallies may be performed, until the consequence is wholly satisfactory and 100 % correct.
Live Cutover: the executing of all undertakings required to fix BSC CRM for the go-live of a peculiar release. A big bulk of these undertakings will be related to informations migration.
1.3.3. Datas Cleansing.
Before informations can be successfully migrated it data demands to be clean, informations cleaning is hence an of import component of any informations migration activity:
Data demands to be in a consistent, standardised and right formatted to let successful migration into CRM ( e. g. CRM holds references as structured references, whereas some bequest systems might keep this information in a freeform format )
Data demands to be complete, to guarantee that upon migration, all Fieldss which are compulsory in CRM are populated. Any Fieldss flagged as mandatary, which are left clean, will do the migration to neglect.
Data demands to be de-duplicated and be of sufficient quality to let efficient and right support of the defined concern procedures. Duplicate records can either be marked for omission at beginning ( preferable option ) , or should be excluded in the extract/conversion process. A.
Legacy informations Fieldss could hold been misused ( keeping information different from what this field was ab initio intended to be used for ) . Data cleaning should pick this up, and a determination needs to be made whether this information should be excluded ( i. e. non migrated ) , or transferred into a more appropriate field.
It is the duty of the information proprietor ( i. e. MOM ) to guarantee the informations provided to the STEE-Info for migration into BSC CRM ( whether this is from a bequest beginning or a templet populated specifically for the BSC CRM ) is accurate.
Datas cleaning should, wherever possible, be done at beginning, i. e. in the bequest systems, for the undermentioned grounds:
Unless a information alteration freezing is put in topographic point, extracted datasets become out of day of the month every bit shortly as they have been extracted, due to updates taking topographic point in the beginning system. When re-extracting the information at a ulterior day of the month to acquire the most recent updates, informations cleansing actions will acquire overwritten. Therefore cleaning will hold to be repeated each clip a new dataset is extracted. In most instances, this is impractical and requires a big attempt.
Data cleaning is typically a concern activity. A Therefore, cleansing in the existent bequest system has the advantage that concern people already have entree to the bequest system, and are besides familiar with the application. Something that is non the instance when information is stored in presenting areas. A In certain instances it may be possible to develop a programme to make a certain grade of machine-controlled cleansing although this adds extra hazard of informations mistakes.
If informations cleaning is done at beginning, each clip a new ( i. e. more recent ) infusion is taken, the consequences of the latest cleaning actions will automatically come across in the infusion without extra attempt.
1.3.4. Pre-Migration Testing.
Testing interruptions down into two nucleus capable countries: logical mistakes and physical mistakes. Physical mistakes are typically syntactical in nature and can be easy identified and resolved. Physical mistakes have nil to make with the quality of the function attempt. Rather, this degree of proving is covering with semantics of the scripting linguistic communication used in the transmutation attempt. Testing is where we place and decide logical mistakes. The first measure is to put to death the function. Even if the function is completed successfully, we must still inquire inquiries such as:
How many records did we anticipate this book to make?
Did the correct figure of records get created?
Has the informations been loaded into the right Fieldss?
Has the informations been formatted right?
The fact is that informations mapping frequently does non do sense to most people until they can physically interact with the new, populated informations constructions. Frequently, this is where the bulk of transmutation and function demands will be discovered. Most people merely do non recognize they have missed something until it is non at that place any longer. For this ground, it is critical to unleash them upon the populated mark informations constructions every bit shortly as possible. The information migration proving stage must be reached every bit shortly as possible to guarantee that it occurs prior to the design and edifice stages of the nucleus undertaking. Otherwise, months of development attempt can be lost as each extra migration demand easy but certainly wreaks mayhem on the information theoretical account. This, in bend, requires substantial alterations to the applications built upon the informations theoretical account.
1.3.5. Migration Validation.
Before the migration could be considered a success, one critical measure remains: to formalize the post-migration environment and confirm that all outlooks have been met anterior to perpetrating. At a lower limit, web entree, file permissions, directory construction, and database/applications need to be validated, which is frequently done via non-production testing. A Another good scheme to formalize package migration is to benchmark the manner concern maps pre-migration and so compare that benchmark to the behavior after migration. The most effectual manner to roll up benchmark measurings is roll uping and analysing Quality Metrics for assorted Business Areas and their corresponding personal businesss.
1.3.6. Data Conversion Process.
Mapped information and information transition plan will be put into usage during this period. Duration and timeframe of this procedure will depend on:
Sum of informations to be migrated.
Number of bequest system to be migrated.
Resources restriction such as waiter public presentation.
Mistake which were churned out by this procedure.
The transition mistake direction attack aims to reject all records incorporating a serious mistake every bit shortly as possible during the transition attack. Correction installations are provided during the transition ; where possible, these will utilize the bing amendment interface.
Mistakes can be classified as follows:
Fatal mistakes – which are so serious that they prevent the history from being loaded onto the database. These will include mistakes that cause a breach of database unity ; such as duplicate primary keys or invalid foreign cardinal mentions. These mistakes will be the focal point of informations cleansing both before and during the transition. Attempts to rectify mistakes without user interaction are normally ineffectual.
Non-fatal mistakes – which are less serious. Load the affected mistake onto the database, still incorporating the mistake, and the mistake will be communicated to the user via a work direction point attached to the record. The mistake will so be corrected with information from user.
Auto-corrected mistakes – for which the offending informations point is replaced by a antecedently agreed value by the transition faculties. This is done before the transition procedure starts together with user to find values which need to be updated.
One of the of import undertakings in the procedure of informations transition is data proof. Data proof in a wide sense includes the checking of the interlingual rendition procedure per Se or look intoing the information to see to what degree the transition procedure is an information continuing function.
Some of the common confirmation methods used will be:
Fiscal confirmations ( verifying pre - to post-conversion sums for cardinal fiscal values, verify subordinate to general leger sums ) – to be conducted centrally in the presence of histories, audit, conformity & A ; hazard direction ;
Compulsory exclusions confirmations and rectifications ( on those exclusions that must be resolved to avoid production jobs ) – to be reviewed centrally but subdivisions to put to death and corroborate rectifications, once more, in the presence of web direction, audit, conformity & A ; hazard direction ;
Detailed confirmations ( where full inside informations are printed and the users will necessitate to make random elaborate confirmations with bequest system informations ) – to be conducted at subdivisions with concluding verification sign-off by subdivision deployment and subdivision director ; 과.
Electronic files fiting ( fiting field by field or record by record ) utilizing pre-defined files.
1.4. Data Migration Method.
The primary method of reassigning informations from a bequest system into Siebel CRM is through Siebel Enterprise Integration Manager ( EIM ).A This installation enables bidirectional exchange of informations between non Siebel database and Siebel database. It is a server constituent in the Siebel eAI constituent group that transfers informations between the Siebel database and other corporate informations beginnings. This exchange of information is accomplished through intermediary tabular arraies called EIM tabular arraies. The EIM tabular arraies act as a presenting country between the Siebel application database and other informations sources. A.
The undermentioned figure illustrates how informations from HPSM, CAMS, and IA databases will be migrated to Siebel CRM database.
1.5. Data Conversion and Migration Schedule.
Following is proposed informations transition and migration agenda to migrate HPMS and CAMS, and IA databases into Siebel CRM database.
1.6. Hazards and Premises.
1.6.1. Hazards.
MOM may non be able to confidently accommodate big and/or complex informations sets. Since the information migration will necessitate to be reconciled a lower limit of 3 times ( system trial, test cutover and unrecorded cutover ) the attempt required within the concern to comprehensively prove the migrated information set is important. In add-on, proficient informations lading restraints during cutover may intend a limited clip window is available for rapprochement undertakings ( e. g. nightlong or during weekends ) MOM may non be able to comprehensively cleanse the bequest informations in line with the BSC CRM undertaking timescales. Since the migration to BSC CRM may be dependent on a figure of cleansing activities to be carried out in the bequest systems, the attempt required within the concern to accomplish this will increase proportionally with the volume of informations migrated. Failure to finish this exercising in the needed timescale may ensue in informations being unable to be migrated into BSC CRM in clip for the planned cutover. The volume of informations mistakes in the unrecorded system may be increased if rapprochement is non completed to the needed criterion. The larger/more composite a migration becomes, the more likely it is that anomalousnesss will occur. A Some of these may ab initio travel undetected. A In the best instance such informations issues can take to a concern and undertaking operating expense in rectifying the mistakes after the event. In the worst instance this can take to a concern runing on inaccurate informations. The more informations migrated into BSC CRM makes the cutover more complex and drawn-out ensuing in an increased hazard of non being able to finish the migration undertaking on time. A Any farther resource or proficient restraints can add to this hazard. Due to the volume of the undertaking, informations migration can deviate undertaking and concern resources off from cardinal activities such as initial system physique, functional testing and user credence testing.
1.6.2. Premises.
Data Access – Entree to the informations held within the CAMS, HPSM and IA applications are required to enable informations profiling, the designation of informations beginnings and to compose functional and proficient specifications. Access connexion is required to HPMS and CAMS, and IA databases to enable executing of informations migrations books. MOM is to supply workstations to run ETL books for the informations migration of HPMS and CAMS, and IA databases. There must non be any schema alterations on bequest HPMS and CAMS, and IA databases during informations migration stage. MOM is to supply sample of production informations for proving the developed ETL books. MOM concern resource handiness ;
Required to help in informations profiling, the designation of informations beginnings and to make functional and proficient specifications.
Required to develop and run informations infusions from the CAMS & A ; HPSM systems.
Required to validate/reconcile/sign-off informations tonss.
Required for informations cleansing.
Data cleaning of beginning informations is the duty of MOM. A STEE-Info will assist place the information anomalousnesss during the informations migration procedure ; nevertheless STEE-Info will non cleanse the information in the CAMS & A ; HPSM applications. A Depending on the information quality, informations cleaning can necessitate considerable attempt, and affect a big sum of resources. The range of the information migration demands has non yet been finalised, as informations objects are identified they will be added on to the informations object registry.
관련 게시물:
최근 게시물.
Chapter 14: The Spread of Infection – Disease Transmission / Contact Transmission, Vehicle Transmission, Vector Transmission.
Multivariable Calculus Chapter 17: Vector Calculus Definitions.
Data conversion migration strategy
This document provides you with a procedure to assist you organizing and performing the data transfer from the legacy system.
It describes a methodology for data migration I used successfully in different implementations. It is based upon my previous experiences. There is no warranty on its content or on the results. This guide gives you suggestions. It is up to you to take the hints and make up your own methodology.
Common Terminology and Abbreviations in Migration Projects:
Note: The terms SAP and R/3 are both use interchangeably to refer to SAP R/3 system.
Big Five : When referring to the Big Five, it means Material Master, Customer Master, Vendor Master, Bill Of Materials (BOM) and Routings.
Business Objects : To help in the analysis and transfer process, the data are not treated as tables or field contents but rather as objects in term of business operational. These are called Business Objects.
Business Object DC responsible : Responsible of the conversion process (Legacy data source and integrity, mapping, conversion rules, etc.) and for the respect of the planned schedule for his Business Object.
Business Object Owner : The one that owns the information in the everyday business. This is the person that will make the strategic choices on functional requirements for the business object and that will do the final validation of the converted data. Can be identified by finding “The highest hierarchical person who will be directly and mostly affected if the business object does not work”
Data Conversion & Data Migration : The data conversion process. “Data conversion” and “Data Migration” terms are used interchangeably in the document.
DC : Abbreviation for the data conversion process.
Domain : Functional domain within the project, like Finance, Sales, Production, etc.
Flat File : A file format used to import data into SAP. The flat file is a plain text file with a tab separator between fields. It can be easily generated from Excel or Access.
Intermediate file : An Excel, Access or other type of file, which is manually manipulated in a process between the LS extraction and the flat file generation.
LSMW : Legacy System Migration Workbench. It is a SAP tool for conversion that permits data loading using flat files extracted from the Legacy System.
Cross reference table or X-Ref table : A table that shows the relation between fields when one value is related to a parent field. For example, the “Sales Organization” will be set accordingly to the material type.
WBS : Work Breakdown Structure.
Implementing SAP is an important challenge, both in terms of resources (people, money, time) and in business process. A lot is at stake and, for most of you, failure is not an option you can afford. To put all odds on your side, you need a good methodology. One that will provide you with a realistic planning, a solid organization, a way to manage the process and control tools to detect and correct slippage before it becomes a problem.
Before you even start to work on specs, you must first get organized. Getting a good planning and organization structure take about two weeks for the first draft , which will leave you with some questions on project organization. Getting a complete and final planning will take at least one more week. Any unsolved issues on these will haunt you throughout the project, so finish this completely before stating any other step.
The data conversion requires functional and technical resources from most departments. These same resources will most probably be involved in other part of the project. For this reason, the risk of conflicting task is high and can quickly lead to a bottleneck where key peoples are overloaded. For this reason, you should consider the data conversion as a project within the project. This translates into the preparation of a complete conversion plan that will help you go through the process and will permit to foresee and solve the conflicting resources usage before the bottleneck ever occurs.
The main steps of the data conversion are:
Organization of the data conversion (Project manager & data conversion coordinator)
Data conversion plan The WBS with workload estimates The calendar planning with resources loading.
Going on with the Business Objects data conversion (The resource responsible of the Business Object DC)
Data Purging and Cleansing Mapping and conversion rules Extract and Load Programs from rules Data and Rules Adaptation (adjusting rules and programs following testing) Load Unit Testing (unitary testing – small volume of manual data) Extract and Load Full size testing (data test and validation – large volume with real extracted data) Full data loading into ACCEPTANCE SYSTEM Full data loading into PRE PRODUCTION SYSTEM Validation of converted data and Key User + Business Objects Owner Signoff Full conversion into PRODUCTION SYSTEM and final Signoff.
Data Conversion Plan.
Business Objects.
A Business object is a general category for data that defines something like material master, vendor master, stocks, orders, purchase requisitions or organizational units. The first step is identifying which business objects (Objects) are required in your SAP implementation.
There are three types of data involved in a SAP system: master data, transactional data, and historical data.
Master Data. Application master data tends to be more static once defined. Most master data can be driven by the legacy applications. Examples include vendors, customers, charts of accounts, assets, bills of materials, material masters, info records, and so on. Transactional Data. Transactional data is current and outstanding transaction data that needs to be captured from the legacy system and defined to the SAP R/3 applications for business process completion. Examples include accounting documents, open purchase orders, open sales orders, back orders, and so on. 과거 데이터. Historical data needs to be brought over from the legacy system to the SAP R/3 System for reference purposes. Examples include closed purchase orders, closed sales orders, summary general ledger information, and so on.
Information to complete the conversion plan.
What Which business objects will be converted from the legacy system into SAP. Where Where are the data, which Legacy Systems are involved for the extraction. How much Estimate the number of records to be ultimately loaded into SAP. How There are two aspects to be considered : The way data is extracted from the Legacy System Automatically extracted from the Legacy system without manual intervention. Manually filled spreadsheet Combination of an automatic Legacy System extraction + Manual Entry into a spreadsheet The way data is injected into SAP : Automatic data transfer from a flat file into SAP Manually entering data with online transactions into SAP Combination of both.
The data transfer method you choose will determine the types of resources you need. For example, you may need temporary employees for the manual data entry and programmers for writing your own extraction programs. You need to know both what data is in your legacy system and which SAP applications correspond to the business objects that will be transferred. One person does not have to know all of this, but the people who know this information should work closely together .
Who Who is involve on each Business Object : Key user (Functional responsible of BO conversion : Rules, manual data corrections, test, validations) Consultant Responsible of data cleaning and purging in the Legacy System Responsible of the extraction Responsible of loading data in SAP Business Object Manager (Hierarchic owner who is responsible of day to day use and integrity of information and the one which will be signing off for data acceptance)
Main Business Objects sequence of conversion:
CONVERTING A BUSINESS OBJECT :
Data Purging and Cleansing.
The purging and cleansing of the Legacy System will save you lot of time and effort in the following steps of the conversion. Start this as soon as possible and do as much as possible. This can be done without specific knowledge of SAP.
Before transferring data from your legacy system, delete all the old and obsolete data. For example, you may delete all one-time customers or those for which there were no transaction in the last two years, also delete unused materials.
This process corrects data inconsistencies and ensures the integrity of the existing data during the migration process. For example, there are often lots of inconsistencies in Customer and Vendor address fields. You will quickly find that SAP will not let you load any address fields unless you get them clean.
Mapping and Conversion Rules.
The documentation of each business object will contain the Data conversion rules (or specification), which include:
* Legacy sources and extraction procedures.
From which Legacy system(s) are we extracting the data and how. Document here specific steps that need to be taken.
What are the cleaning steps to be taken and extraction filters to be used.
Guidelines to apply or rules that is used by many fields (thus avoiding to retype it and making updating easier as it is only in one place).
Which SAP fields to use and how do we get the final value for each SAP field.
General rules are the one that does not yield directly to a field value. For example the way in which we differentiate the material types in the Legacy System is such a rule. Field rules are those that give a value for a specific field.
This is a crucial one. When discussing or writing notes, ALWAYS refer to a field in the form TABLE-FIELD. You will quickly realize that as the project go, different people will start using different names for the same field. As well they may start using the same name for different fields.
On top of this, some fields exist in different views in SAP master data. Sometime it is the same field that is shown at two places while other times it is really two different fields. The best way to know which case apply is to have the TABLE + FIELD information.
In Material Master, the field «Availability check» exists in the “MRP2” and the “Sales Gen” views. If you look at the TABLE-FIELD of each view you get :
Sales Gen : MARC-MTVFP.
In both cases the TABLE-FIELD name is the same, so it is the same field.
In Customer Master, the field ” Terms of Payment’ exist in “Payment Transactions” and “Billing” views. If you look at the TABLE-FIELD of each view you get :
Payment Transactions : KNVV - ZTERM.
Billing Views : KNB1- ZTERM.
It is not the same field. In the payment view, the field is linked to the Company Code while for the Billing view it is linked to the Sales Organization (you find this by looking at the tables keys). So both of these fields can have different values.
Technical Methodology.
A special case for Material Master.
Material Master involves all the domains and may require anywhere from 20 fields to a few hundreds depending on the complexity of your implementation. Some fields will be used by different domains while others will be used by only one domain but its value will have an impact on functionality used by another domain.
This is the most complex Business Object to document and, at the same time, it is the one you must start with in you conversion process.
1st step : Selection of the fields by each domain.
Get each domain with their consultants to go through the mapping file and look at the fields for each material type. The goal here is to see all the fields that are important and ask questions to understand them. This is done separately by each domain and documented in different mapping files. At these points we are not interested about where the values will come from and how will we get them. JUST GET THE MAPPING DONE and work on understanding what material master is. Each time a domain select a field for a specific material type, they must enter their domain type in the list. Here are some (theoretical) examples of mapping from MM, PP and SD.
In Material Master , some fields can be entered / modified in different views. For example, the field “Goods receipt processing time in days (MARC-WEBAZ)” exists in views Purchasing, MRP2 and Quality management. When doing the rules and the load program, the same field can’t be in different views. To solve this, proceed as follow:
See with all implicated domains who are the lead for the field and decide in which view the field should be included.
Taking the example of the field “Goods receipt processing time in days (MARC-WEBAZ)”, it can be decided among the domains to put it in the Purchasing view (and nowhere else).
Material Master Conversion:
High Level Process Design.
These are all the major views involved in Material Master Object:
Basic Data Alternative UOM Inspection Text Classification Sales Organization Sales General Plant Purchasing Foreign Trade Import & Export APO Master Data MRP1 & 2 Quality Management Accounting.
Usually the Function specification Owners will do the recording method to capture all the fields on the above views and prepare the Mapping Logic.
The most complex design involves in Plant merging and Classification Merging . (Refer High Level Process Document)
A member group of the type customer segment group is a collection of users, as defined by the Seller or merchant, who share a common interest.
For Eg: A mining Company has CSG’s like Cerro Matoso( CMSA ),Met Coal ( MTCO ),Base Metals ( BASE ) etc.,
Based on CSG’s the data need to be split up before loading through LSMW for valuation.
The split logic can be done by Loop Component in Business Objects Data Services.
Get the distinct CSG’s in a dataflow. Assign a variable for the sequence number for the max value and loop from the initial.
Other Business Objects Conversion:
For the other BO, because they are simpler than Material Master and involve fewer people, we will start directly with the Conversion rules document. It is in this document that we will both, decide which fields we need and, in a second step, start working on the rules.
Here are some samples of BO conversion rules.
BOM conversion rules sample.
Open Account Receivable conversion rules sample.
Vendor Master conversion rules sample.
Note that SAP term “Security deposit” equal “Retention” in PRMS.
Type of transaction.
TYPE field in PRMS :
Any other type is an error.
Validation to apply both at extraction and load.
Partial PMT………. must be negative in PRMS, if not ERROR.
Credit Memo………must be negative in PRMS, if not ERROR.
Debit Memo……….must be positive in PRMS, if not ERROR.
Any other type is an ERROR.
LSM Load parameters.
KTOPL – Chart of account : CA00.
BUKRS – Company code: 0070.
GSBER – Business Area : 0040.
BUDAT – Posting Date : “05-31-02” or last day of last closed period.
OFFSET – Account (2) : REPRISECL.
SKPERR – Skip err : X.
L egacy S ystem M igration W orkbench (LSMW):
LSMW is used for migrating data from a legacy system to SAP system, or from one SAP system to another.
Apart from standard batch/direct input and recordings, BAPI and IDocs are available as additional import methods for processing the legacy data.
The LSMW comprises the following main steps:
Read data (legacy data in spreadsheet tables and/or sequential files). Convert data (from the source into the target format). Import data (to the database used by the R/3 application.
But, before these steps, you need to perform following steps:
Define source structure: structure of data in the source file. Define target structure: structure of SAP that receives data. Field mapping: Mapping between the source and target structure with conversions, if any. Specify file: location of the source file.
Methods used for data migration like BDC, LSMW and Call Transaction.
All the 3 methods are used to migrate data. Selection of these methods depends on the scenario, amount of data need to transfer. LSMW is a ready tool provided by SAP and you have to follow some 17 steps to migrate master data. While in BDCs Session method is the better choice because of some advantages over call transaction. But call transaction is also very useful to do immediate updation of small amount of data. (In call transaction developer has to handle errors).
SO Bottom line is make choice of these methods based of real time requirements.
These methods are chosen completely based on situation you are in. Direct input method is not available for all scenarios else, they are the simplest ones. In batch input method, you need to do recording for the transaction concerned. Similarly, IDoc, and BAPI are there, and use of these need to be decided based on the requirement.
Try to go through the some material on these four methods, and implement them. You will then have a fair idea about when to use which.
BDC – It is Batch data communication. It’s used for data conversion from legacy system to SAP system. Only technical people can do it. Tcode is SHDB .
LSMW – It is legacy system migration workbench. Its also used for data conversion from legacy system to SAP system. But it is role of functional consultant.
There are 14 steps in LSMW. As soon as you complete the one step, automatically it will go to next step.
In general you can use LSMW. But if you want to transfer more than 40,000 data, then it is not possible in LSMW. That time you can take help of BDC.
LSMW data migration for sales order VA01 / XD01 customer.
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SAP offer free content to help migrate data in SAP (ERP, CRM, etc.). See websmp103.sap-ag. de/rds-dm2erpcrm.
This is indeed a good explaination for data migration process.
Very informative article (probably the best). Keep Posting.
A nice, structured and well written document.
Great piece of literature.
Thanks for sharing the knowledge.
good article Johnpaul !
Wow Johnpaul this is a great article! It’s very informative and goes through a lot of what is required for a successful migration. At Method360 we notice that a lot of people don’t spend the requisite amount of time planning for the migrations and end up having to backtrack and spend a lot of time re-doing things that should have been done much earlier, especially in the data purging and cleansing steps. Clients think that once they get transferred to the newer system that everything will be fixed, but end up with a slow system with a lot of errors. Spending the time to review your historical and master data that may have changed or is no longer necessary can really speed up your systems. In order to help out clients understand everything they need to be successful we created a free workshop. Feel free to give it a look!
What is the difference between data conversion and data migration?
Asked on: May 9th, 2006.
Showing 1 - 1 of 1 Ans Vijayveer Singh.
Answered On : May 24th, 2006.
Data Migration is upgrading from one version to another version fro e. g. from 11.5.9 to 11.5.10.. Data Conversion is receiving data from a legacy system or receiving data from another module ( e. g. PA), validating it and converting it to ur our the target module using the standard import program.
Answered On : May 25th, 2006.
Are there any Migration tools that can make the job easier. What are the steps.
Answered On : Oct 10th, 2006.
Data Conversion refers to the movement of data from a legacy system or application, to a replacement application or sub-system. Data migration refers to movement of data from one database to another database, but not neccesarily to a working application or subsystem tables. Other important terms pertaining to data include;1. Data Cleansing2.Data Integration3.Data replication4. Data Intergrity Testing5.Data Transfer6.Data Transformation7.Data Translation8. Data Partioning.
Answered On : Jan 6th, 2010.
Data Migration is a process of moving required (and most often very large) volumes of data from our clients' existing systems to new systems. Existing systems can be anything from custom-built IT infrastructures to spreadsheets and standalone databases. Data conversion can be defined as a process of converting data from one structural form to another to suit the requirements of the system to which it is migrated. Approach used for Data Conversion:1. Conversion Data Mapping ( map to specify the data of legacy system with data of oracle ERP system ).2. Download Programs ( programs to extract data from database and insert into the Flat file ).3. ASCII Flat File (Flat file / Text file).4. Upload Program5.Interface Tables a) Description of Interface Table. b) Creation of Interface Table.6. Translation Programs7. Interface Programs8. Application Production Table9. Testing10. Write and Perform Conversion Execution Plan. Thanks, Bonthu Nagi Reddy.
Answered On : Jan 29th, 2013.
Informatics Outsourcing is an Offshore Data Management service company. Data Management Service includes all types of Data Conversion, File Conversion, XML Conversion, HTML Conversion, SGML Conversion, Document Conversion, Data Entry, Data Extraction and Validation, OCR and ICR Services with affordable price. Our team to give the solution quickly and given requirements.
Answered On : Aug 26th, 2014.
As an integral part of your team, White Box will provide value throughout the life-cycle of your data management project while minimizing risk. Throughout the process, we are committed to providing your company with superior customer service. Quality control and execution are at the center of everything we do. Here is an illustration to the entire data conversion process: See the illustration below for a step-by-step view of the entire data conversion process.
Answered On : Dec 13th, 2017.
Data conversion is a translation process where data from one format is translated to another so that it can be used in SAP system.
이 세분화의 범위는 CRM 위치에서 정보 이전 계획을 지정하는 것입니다. 진정으로 본질적으로 CRM은 유증기 시스템을 BSC CRM으로 전면 교체하는 것이 아니라 대신 빙 응용 프로그램 환경에서 클라이언트 상호 작용의 조정 및 방향을 제시합니다. 따라서 전통적 의미에서 큰 눈금 표 정보 이전은 필요하지 않으며 단지 소수의 정보 항목 만 BSC CRM으로 마이그레이션해야합니다.
데이터 이전은 일반적으로 '일회성'입니다. 라이브 이전에 활동. 자주 또는 임시 위주로 요구되는 진행중인 모든 정보는 인터페이스로 간주되며 정보 이전 범위의 일부가 아닙니다.
이 하위 절에서는 STEE-Infosoft가 CAMS 및 HPSM 유증 시스템에서 BSC CRM 시스템으로 정보를 마이그레이션하는 방법을 설명합니다.
STEE-InfoSoft는 CAMS 및 HPSM의 현재 유증기 데이터베이스를 마이그레이션하기위한 포괄적 인 정보 전환 및 마이그레이션 솔루션을 제공합니다. 이 솔루션은 입증 된 방법론 분석 및 전문 지식을 활용하여 데이터베이스 마이그레이션에 가장 적합하고 적합한 엔지니어링을 따릅니다. STEE-InfoSoft의 정보 마이그레이션 방법론 분석은 고객에게 결과의 품질, 일관성 및 진실성을 보장합니다.
표 11은 방법 론적 분석을 활용 한 STEE-InfoSoft 정보 마이그레이션 가치 제안을 보여줍니다.
표 11 : STEE-Infosoft 정보 마이그레이션 가치 제안.
세부 정보.
비용 효과적.
STEE-InfoSoft는 비용 효율적인 정보 마이그레이션 솔루션을 채택합니다. 정보 마이그레이션을 위해 최소한의 중단 시간을 달성 할 수 있습니다. 기계화 속도를 광범위하게 사용하여 작업을 향상시키고 실행 후 변경 및 보정을 실용적으로 만듭니다. 잘못 된 후행 및 수정 기능은 다년간 전환 재발생을 피하는 데 도움이됩니다. 사용자 정의를 통해 올바른 방식으로 직업을 획득 할 수 있습니다.
매우 짧은 가동 중지 시간.
대부분의 마이그레이션 절차는 실행중인 응용 프로그램 시스템의 외부에 있으며 정상적인 작업 흐름에 영향을주지 않으므로 가동 중지 시간이 최소화됩니다. 정보 전환이 단계적으로 수행되도록하여 가동 중지 시간을 줄입니다.
데이터 무결성 보증.
스크립트 및 계획은 정보를 테스트하고 형식화 할 때 이후 사용을 위해 자동으로 생성됩니다.
마이그레이션 프로세스 제어.
빙 시스템의 다운 타임을 줄이기 위해 주입 및 부담 절차를 실행하기위한 ETL (Extract, Transform 및 Load) 스크립트 만 작성합니다. Fieldss 통합, 정보 필터링, 정보 분할, 필드 정의 변경 및 필드 내용 해석 추가, 삭제, 변환 및 집계, 정보 정리에 대한 유효성 검사 규정.
1.1. 데이터 마이그레이션 개요.
데이터 마이그레이션은 한 위치, 저장 매체 또는 하드웨어 / 소프트웨어 시스템에서 다른 위치로 정보를 전송하는 것입니다. 이주 시도는 종종 능숙한 하부 구조 또는 관심사 요구의 변경에서 상승에 대한 요구에 의해 촉발된다.
정보 마이그레이션에서 가장 좋은 패턴은 성공적인 정보 마이그레이션을 위해 내장 된 두 가지 규칙을 권장합니다.
새로운 (마크) 정보 샵을 설치하는 유일한 목적에 전념하는 사업으로 정보 마이그레이션을 수행하십시오. 데이터 마이그레이션 계획, 데이터 마이그레이션 분석 및 설계, 데이터 마이그레이션 구현, 데이터 마이그레이션 폐쇄 등 네 가지 주요 단계에서 정보 마이그레이션을 수행합니다 (1.1 참조).
애드온에서 성공한 정보 마이그레이션 사업은 기회를 최대화하고 위험을 완화하는 1 초입니다. 아래의 중요한 성공 요인이 확인되었습니다.
정보 마이그레이션을 독립적 인 사업으로 수행하십시오.
절차 전반에 걸쳐 전망을 수립하고 관리하십시오.
현재와 미래의 정보와 관심사에 대한 이해.
전문 지식을 가진 사람을 유증 정보를 부르는 사람으로 식별하십시오.
유증 증서를 사용할 수있는 인증서를 수집하십시오.
역할을 수행하는 정보 이전 정의 & # 038; A; 의무.
정보 내용, 품질 및 구성에 대한 포괄적 인 개요를 수행하십시오.
관심사 정보 및 정보 품질의 중요성을 파악하기 위해 관심 소유자 및 이해 관계자와 협력하십시오.
1.2. STEE-Info 데이터 마이그레이션 프로젝트 수명주기.
표 12는 STEE-Info 데이터 마이그레이션 프로젝트 수명주기의 각 단계에 대한 상위 단계 절차를 나열합니다.
모든 정보 마이그레이션 작업이 데이터 마이그레이션 프로젝트 수명주기의 네 단계를 따르지만 상위 및 하위 절차는 각 마이그레이션 프로젝트의 크기, 범위 및 복잡성에 따라 달라질 수 있습니다. 따라서 아래 정보는 정보 마이그레이션 시도를 개발, 측정 및 구현하기위한 가이드 라인. 각 상위 및 하위 절차는 Datas Migration Plan에 포함되어야합니다. 적절한 것으로 간주되지 않는 절차의 경우 제외에 대한 정당성을 Datas Migration Plan에 문서화해야합니다.
도표 12 : 확인 된 고위 기업을 가진 자료 이동 프로젝트 수명주기.
데이터 마이그레이션 계획 단계.
데이터 마이그레이션 분석 & # 038; A; 디자인 단계.
데이터 마이그레이션 구현 단계.
데이터 마이그레이션 종료 단계.
계획 데이터 마이그레이션 프로젝트.
평가 결과 분석.
문서 데이터 마이그레이션 결과.
데이터 마이그레이션 요구 사항 결정.
보안 컨트롤 정의.
문서화 된 교훈.
현재 환경 평가.
디자인 데이터 환경.
지식 이전을 수행하십시오.
데이터 마이그레이션 계획 개발.
마이그레이션 절차 설계.
변환 데이터 변환 (필요에 따라)
데이터 마이그레이션 결과를 전달합니다.
팀 역할 및 직무 정의 및 할당.
데이터 품질 검증.
데이터 마이그레이션 (평가판 / 배포)
마이그레이션 결과 검증 (반복)
마이그레이션 후 결과의 유효성 확인.
정보 이전 사업의 라이프 사이클 동안, 분대는 1.2에 나와있는 활동을 통해 정보를 이동시킵니다.
팀은 새로운 마크 정보 상점에 성공적인 정보 부담을 보장하기 위해 필요에 따라 이러한 정보 방향 활동을 반복합니다.
1.3. 데이터 마이그레이션 지침.
1.3.1. 데이터 마이그레이션 접근법.
1.3.1.1. 마스터 데이터 & # 8211; (예 : 고객, 자산)
공격은 마에스트로 정보가 CRM으로 마이그레이션되어 이러한 조건을 제공한다는 것입니다.
정보가있는 응용 프로그램이 CRM으로 대체됩니다.
마에스트로 레코드는 사후에 CRM 기능을 백업하는 데 필요합니다.
기 본적 인 운영, 적용 범위 또는 법적 / 법정 요구가 있습니다.
마에스트로 정보가 최신 정보입니다 (누락 된 것으로 표시된 레코드는 이전 할 필요가 없음) 또는 다른 이전을 백업해야합니다.
유증 정보는 일상적인 CRM 시스템 실행에 악영향을 미치지 않는 정도의 충분한 품질을 지니고 있거나 비즈니스 요구 사항에 부합하도록 정보 마이그레이션 절차에서 충분히 개선 / 개선 될 것입니다.
Note: Where the maestro informations resides in an application that is non being replaced by CRM, but is required by CRM to back up specific functionality, the informations will NOT be migrated but accessed from CRM utilizing a dynamic query look-up. A dynamic question look-up is a real-time question accessing the information in the beginning application as and when it is required. A The advantages of this attack are ;
Avoids the duplicate of informations throughout the system landscape.
Avoids informations within CRM going out-of-date.
Avoids the development and running of frequent interfaces to update the informations within CRM.
Reduces the measure of informations within the CRM systems.
1.3.1.2. ‘Open ‘ Transactional informations ( e. g. Service Tickets )
The attack is that ‘open ‘ transactional informations will NOT be migrated to CRM unless ALL these conditions are met:
There is a cardinal operational, coverage or legal/statutory demand.
The bequest system is to be decommissioned as a consequence of the BSC CRM undertaking in timescales that would forestall a ‘run down ‘ of unfastened points.
The parallel ‘run down ‘ of unfastened points within the bequest system is impractical due to operational, timing or resource restraints.
The CRM physique and structures permit a correct and consistent reading of bequest system points aboard CRM-generated points.
The concern proprietor is able to perpetrate resources to have informations rapprochement and sign-off at a elaborate degree in a timely mode across multiple undertaking stages.
1.3.1.3. Historical Maestro and Transactional informations.
The attack is that historical informations will non be migrated unless ALL these conditions are met:
There is a cardinal operational, coverage or legal/statutory demand that can non be met by utilizing the staying system.
The bequest system is to be decommissioned as a direct consequence of the BSC CRM undertaking within the BSC CRM undertaking timeline.
An archiving solution could non run into demands.
The CRM physique and structures permit a correct and consistent reading of bequest system points aboard CRM-generated points.
The concern proprietor is able to perpetrate resources to have informations rapprochement and sign-off at a elaborate degree in a timely mode across multiple undertaking stages.
1.3.2. Data Migration Testing Cycles.
In order to prove and verify the migration procedure it is proposed that there will be three proving rhythms before the concluding unrecorded burden:
Trial Load 1: Unit of measurement testing of the infusion and burden modus operandis.
Trial Load 2: The first trial of the complete end-to-end informations migration procedure for each information entity. The chief intent of this burden is to guarantee the extract modus operandis work right, the presenting country transmutation is right, and the burden modus operandis can lade the information successfully into CRM. The assorted information entities will non needfully be loaded in the same sequence as will be done during the unrecorded cutover.
Trial Cutover: a complete dry run of the unrecorded informations migration procedure. The executing will be done utilizing the cutover program in order to formalize that the program is sensible and possible to finish in the in agreement timescale. A concluding set of cleansing actions will come out of test cutover ( for any records which failed during the migration because of informations quality issues ) . There will be at least one test cutover. For complex, bad, migrations several test tallies may be performed, until the consequence is wholly satisfactory and 100 % correct.
Live Cutover: the executing of all undertakings required to fix BSC CRM for the go-live of a peculiar release. A big bulk of these undertakings will be related to informations migration.
1.3.3. Datas Cleansing.
Before informations can be successfully migrated it data demands to be clean, informations cleaning is hence an of import component of any informations migration activity:
Data demands to be in a consistent, standardised and right formatted to let successful migration into CRM ( e. g. CRM holds references as structured references, whereas some bequest systems might keep this information in a freeform format )
Data demands to be complete, to guarantee that upon migration, all Fieldss which are compulsory in CRM are populated. Any Fieldss flagged as mandatary, which are left clean, will do the migration to neglect.
Data demands to be de-duplicated and be of sufficient quality to let efficient and right support of the defined concern procedures. Duplicate records can either be marked for omission at beginning ( preferable option ) , or should be excluded in the extract/conversion process. A.
Legacy informations Fieldss could hold been misused ( keeping information different from what this field was ab initio intended to be used for ) . Data cleaning should pick this up, and a determination needs to be made whether this information should be excluded ( i. e. non migrated ) , or transferred into a more appropriate field.
It is the duty of the information proprietor ( i. e. MOM ) to guarantee the informations provided to the STEE-Info for migration into BSC CRM ( whether this is from a bequest beginning or a templet populated specifically for the BSC CRM ) is accurate.
Datas cleaning should, wherever possible, be done at beginning, i. e. in the bequest systems, for the undermentioned grounds:
Unless a information alteration freezing is put in topographic point, extracted datasets become out of day of the month every bit shortly as they have been extracted, due to updates taking topographic point in the beginning system. When re-extracting the information at a ulterior day of the month to acquire the most recent updates, informations cleansing actions will acquire overwritten. Therefore cleaning will hold to be repeated each clip a new dataset is extracted. In most instances, this is impractical and requires a big attempt.
Data cleaning is typically a concern activity. A Therefore, cleansing in the existent bequest system has the advantage that concern people already have entree to the bequest system, and are besides familiar with the application. Something that is non the instance when information is stored in presenting areas. A In certain instances it may be possible to develop a programme to make a certain grade of machine-controlled cleansing although this adds extra hazard of informations mistakes.
If informations cleaning is done at beginning, each clip a new ( i. e. more recent ) infusion is taken, the consequences of the latest cleaning actions will automatically come across in the infusion without extra attempt.
1.3.4. Pre-Migration Testing.
Testing interruptions down into two nucleus capable countries: logical mistakes and physical mistakes. Physical mistakes are typically syntactical in nature and can be easy identified and resolved. Physical mistakes have nil to make with the quality of the function attempt. Rather, this degree of proving is covering with semantics of the scripting linguistic communication used in the transmutation attempt. Testing is where we place and decide logical mistakes. The first measure is to put to death the function. Even if the function is completed successfully, we must still inquire inquiries such as:
How many records did we anticipate this book to make?
Did the correct figure of records get created?
Has the informations been loaded into the right Fieldss?
Has the informations been formatted right?
The fact is that informations mapping frequently does non do sense to most people until they can physically interact with the new, populated informations constructions. Frequently, this is where the bulk of transmutation and function demands will be discovered. Most people merely do non recognize they have missed something until it is non at that place any longer. For this ground, it is critical to unleash them upon the populated mark informations constructions every bit shortly as possible. The information migration proving stage must be reached every bit shortly as possible to guarantee that it occurs prior to the design and edifice stages of the nucleus undertaking. Otherwise, months of development attempt can be lost as each extra migration demand easy but certainly wreaks mayhem on the information theoretical account. This, in bend, requires substantial alterations to the applications built upon the informations theoretical account.
1.3.5. Migration Validation.
Before the migration could be considered a success, one critical measure remains: to formalize the post-migration environment and confirm that all outlooks have been met anterior to perpetrating. At a lower limit, web entree, file permissions, directory construction, and database/applications need to be validated, which is frequently done via non-production testing. A Another good scheme to formalize package migration is to benchmark the manner concern maps pre-migration and so compare that benchmark to the behavior after migration. The most effectual manner to roll up benchmark measurings is roll uping and analysing Quality Metrics for assorted Business Areas and their corresponding personal businesss.
1.3.6. Data Conversion Process.
Mapped information and information transition plan will be put into usage during this period. Duration and timeframe of this procedure will depend on:
Sum of informations to be migrated.
Number of bequest system to be migrated.
Resources restriction such as waiter public presentation.
Mistake which were churned out by this procedure.
The transition mistake direction attack aims to reject all records incorporating a serious mistake every bit shortly as possible during the transition attack. Correction installations are provided during the transition ; where possible, these will utilize the bing amendment interface.
Mistakes can be classified as follows:
Fatal mistakes – which are so serious that they prevent the history from being loaded onto the database. These will include mistakes that cause a breach of database unity ; such as duplicate primary keys or invalid foreign cardinal mentions. These mistakes will be the focal point of informations cleansing both before and during the transition. Attempts to rectify mistakes without user interaction are normally ineffectual.
Non-fatal mistakes – which are less serious. Load the affected mistake onto the database, still incorporating the mistake, and the mistake will be communicated to the user via a work direction point attached to the record. The mistake will so be corrected with information from user.
Auto-corrected mistakes – for which the offending informations point is replaced by a antecedently agreed value by the transition faculties. This is done before the transition procedure starts together with user to find values which need to be updated.
One of the of import undertakings in the procedure of informations transition is data proof. Data proof in a wide sense includes the checking of the interlingual rendition procedure per Se or look intoing the information to see to what degree the transition procedure is an information continuing function.
Some of the common confirmation methods used will be:
Fiscal confirmations ( verifying pre - to post-conversion sums for cardinal fiscal values, verify subordinate to general leger sums ) – to be conducted centrally in the presence of histories, audit, conformity & A ; hazard direction ;
Compulsory exclusions confirmations and rectifications ( on those exclusions that must be resolved to avoid production jobs ) – to be reviewed centrally but subdivisions to put to death and corroborate rectifications, once more, in the presence of web direction, audit, conformity & A ; hazard direction ;
Detailed confirmations ( where full inside informations are printed and the users will necessitate to make random elaborate confirmations with bequest system informations ) – to be conducted at subdivisions with concluding verification sign-off by subdivision deployment and subdivision director ; 과.
Electronic files fiting ( fiting field by field or record by record ) utilizing pre-defined files.
1.4. Data Migration Method.
The primary method of reassigning informations from a bequest system into Siebel CRM is through Siebel Enterprise Integration Manager ( EIM ).A This installation enables bidirectional exchange of informations between non Siebel database and Siebel database. It is a server constituent in the Siebel eAI constituent group that transfers informations between the Siebel database and other corporate informations beginnings. This exchange of information is accomplished through intermediary tabular arraies called EIM tabular arraies. The EIM tabular arraies act as a presenting country between the Siebel application database and other informations sources. A.
The undermentioned figure illustrates how informations from HPSM, CAMS, and IA databases will be migrated to Siebel CRM database.
1.5. Data Conversion and Migration Schedule.
Following is proposed informations transition and migration agenda to migrate HPMS and CAMS, and IA databases into Siebel CRM database.
1.6. Hazards and Premises.
1.6.1. Hazards.
MOM may non be able to confidently accommodate big and/or complex informations sets. Since the information migration will necessitate to be reconciled a lower limit of 3 times ( system trial, test cutover and unrecorded cutover ) the attempt required within the concern to comprehensively prove the migrated information set is important. In add-on, proficient informations lading restraints during cutover may intend a limited clip window is available for rapprochement undertakings ( e. g. nightlong or during weekends ) MOM may non be able to comprehensively cleanse the bequest informations in line with the BSC CRM undertaking timescales. Since the migration to BSC CRM may be dependent on a figure of cleansing activities to be carried out in the bequest systems, the attempt required within the concern to accomplish this will increase proportionally with the volume of informations migrated. Failure to finish this exercising in the needed timescale may ensue in informations being unable to be migrated into BSC CRM in clip for the planned cutover. The volume of informations mistakes in the unrecorded system may be increased if rapprochement is non completed to the needed criterion. The larger/more composite a migration becomes, the more likely it is that anomalousnesss will occur. A Some of these may ab initio travel undetected. A In the best instance such informations issues can take to a concern and undertaking operating expense in rectifying the mistakes after the event. In the worst instance this can take to a concern runing on inaccurate informations. The more informations migrated into BSC CRM makes the cutover more complex and drawn-out ensuing in an increased hazard of non being able to finish the migration undertaking on time. A Any farther resource or proficient restraints can add to this hazard. Due to the volume of the undertaking, informations migration can deviate undertaking and concern resources off from cardinal activities such as initial system physique, functional testing and user credence testing.
1.6.2. Premises.
Data Access – Entree to the informations held within the CAMS, HPSM and IA applications are required to enable informations profiling, the designation of informations beginnings and to compose functional and proficient specifications. Access connexion is required to HPMS and CAMS, and IA databases to enable executing of informations migrations books. MOM is to supply workstations to run ETL books for the informations migration of HPMS and CAMS, and IA databases. There must non be any schema alterations on bequest HPMS and CAMS, and IA databases during informations migration stage. MOM is to supply sample of production informations for proving the developed ETL books. MOM concern resource handiness ;
Required to help in informations profiling, the designation of informations beginnings and to make functional and proficient specifications.
Required to develop and run informations infusions from the CAMS & A ; HPSM systems.
Required to validate/reconcile/sign-off informations tonss.
Required for informations cleansing.
Data cleaning of beginning informations is the duty of MOM. A STEE-Info will assist place the information anomalousnesss during the informations migration procedure ; nevertheless STEE-Info will non cleanse the information in the CAMS & A ; HPSM applications. A Depending on the information quality, informations cleaning can necessitate considerable attempt, and affect a big sum of resources. The range of the information migration demands has non yet been finalised, as informations objects are identified they will be added on to the informations object registry.
관련 게시물:
최근 게시물.
Chapter 14: The Spread of Infection – Disease Transmission / Contact Transmission, Vehicle Transmission, Vector Transmission.
Multivariable Calculus Chapter 17: Vector Calculus Definitions.
Data conversion migration strategy
This document provides you with a procedure to assist you organizing and performing the data transfer from the legacy system.
It describes a methodology for data migration I used successfully in different implementations. It is based upon my previous experiences. There is no warranty on its content or on the results. This guide gives you suggestions. It is up to you to take the hints and make up your own methodology.
Common Terminology and Abbreviations in Migration Projects:
Note: The terms SAP and R/3 are both use interchangeably to refer to SAP R/3 system.
Big Five : When referring to the Big Five, it means Material Master, Customer Master, Vendor Master, Bill Of Materials (BOM) and Routings.
Business Objects : To help in the analysis and transfer process, the data are not treated as tables or field contents but rather as objects in term of business operational. These are called Business Objects.
Business Object DC responsible : Responsible of the conversion process (Legacy data source and integrity, mapping, conversion rules, etc.) and for the respect of the planned schedule for his Business Object.
Business Object Owner : The one that owns the information in the everyday business. This is the person that will make the strategic choices on functional requirements for the business object and that will do the final validation of the converted data. Can be identified by finding “The highest hierarchical person who will be directly and mostly affected if the business object does not work”
Data Conversion & Data Migration : The data conversion process. “Data conversion” and “Data Migration” terms are used interchangeably in the document.
DC : Abbreviation for the data conversion process.
Domain : Functional domain within the project, like Finance, Sales, Production, etc.
Flat File : A file format used to import data into SAP. The flat file is a plain text file with a tab separator between fields. It can be easily generated from Excel or Access.
Intermediate file : An Excel, Access or other type of file, which is manually manipulated in a process between the LS extraction and the flat file generation.
LSMW : Legacy System Migration Workbench. It is a SAP tool for conversion that permits data loading using flat files extracted from the Legacy System.
Cross reference table or X-Ref table : A table that shows the relation between fields when one value is related to a parent field. For example, the “Sales Organization” will be set accordingly to the material type.
WBS : Work Breakdown Structure.
Implementing SAP is an important challenge, both in terms of resources (people, money, time) and in business process. A lot is at stake and, for most of you, failure is not an option you can afford. To put all odds on your side, you need a good methodology. One that will provide you with a realistic planning, a solid organization, a way to manage the process and control tools to detect and correct slippage before it becomes a problem.
Before you even start to work on specs, you must first get organized. Getting a good planning and organization structure take about two weeks for the first draft , which will leave you with some questions on project organization. Getting a complete and final planning will take at least one more week. Any unsolved issues on these will haunt you throughout the project, so finish this completely before stating any other step.
The data conversion requires functional and technical resources from most departments. These same resources will most probably be involved in other part of the project. For this reason, the risk of conflicting task is high and can quickly lead to a bottleneck where key peoples are overloaded. For this reason, you should consider the data conversion as a project within the project. This translates into the preparation of a complete conversion plan that will help you go through the process and will permit to foresee and solve the conflicting resources usage before the bottleneck ever occurs.
The main steps of the data conversion are:
Organization of the data conversion (Project manager & data conversion coordinator)
Data conversion plan The WBS with workload estimates The calendar planning with resources loading.
Going on with the Business Objects data conversion (The resource responsible of the Business Object DC)
Data Purging and Cleansing Mapping and conversion rules Extract and Load Programs from rules Data and Rules Adaptation (adjusting rules and programs following testing) Load Unit Testing (unitary testing – small volume of manual data) Extract and Load Full size testing (data test and validation – large volume with real extracted data) Full data loading into ACCEPTANCE SYSTEM Full data loading into PRE PRODUCTION SYSTEM Validation of converted data and Key User + Business Objects Owner Signoff Full conversion into PRODUCTION SYSTEM and final Signoff.
Data Conversion Plan.
Business Objects.
A Business object is a general category for data that defines something like material master, vendor master, stocks, orders, purchase requisitions or organizational units. The first step is identifying which business objects (Objects) are required in your SAP implementation.
There are three types of data involved in a SAP system: master data, transactional data, and historical data.
Master Data. Application master data tends to be more static once defined. Most master data can be driven by the legacy applications. Examples include vendors, customers, charts of accounts, assets, bills of materials, material masters, info records, and so on. Transactional Data. Transactional data is current and outstanding transaction data that needs to be captured from the legacy system and defined to the SAP R/3 applications for business process completion. Examples include accounting documents, open purchase orders, open sales orders, back orders, and so on. 과거 데이터. Historical data needs to be brought over from the legacy system to the SAP R/3 System for reference purposes. Examples include closed purchase orders, closed sales orders, summary general ledger information, and so on.
Information to complete the conversion plan.
What Which business objects will be converted from the legacy system into SAP. Where Where are the data, which Legacy Systems are involved for the extraction. How much Estimate the number of records to be ultimately loaded into SAP. How There are two aspects to be considered : The way data is extracted from the Legacy System Automatically extracted from the Legacy system without manual intervention. Manually filled spreadsheet Combination of an automatic Legacy System extraction + Manual Entry into a spreadsheet The way data is injected into SAP : Automatic data transfer from a flat file into SAP Manually entering data with online transactions into SAP Combination of both.
The data transfer method you choose will determine the types of resources you need. For example, you may need temporary employees for the manual data entry and programmers for writing your own extraction programs. You need to know both what data is in your legacy system and which SAP applications correspond to the business objects that will be transferred. One person does not have to know all of this, but the people who know this information should work closely together .
Who Who is involve on each Business Object : Key user (Functional responsible of BO conversion : Rules, manual data corrections, test, validations) Consultant Responsible of data cleaning and purging in the Legacy System Responsible of the extraction Responsible of loading data in SAP Business Object Manager (Hierarchic owner who is responsible of day to day use and integrity of information and the one which will be signing off for data acceptance)
Main Business Objects sequence of conversion:
CONVERTING A BUSINESS OBJECT :
Data Purging and Cleansing.
The purging and cleansing of the Legacy System will save you lot of time and effort in the following steps of the conversion. Start this as soon as possible and do as much as possible. This can be done without specific knowledge of SAP.
Before transferring data from your legacy system, delete all the old and obsolete data. For example, you may delete all one-time customers or those for which there were no transaction in the last two years, also delete unused materials.
This process corrects data inconsistencies and ensures the integrity of the existing data during the migration process. For example, there are often lots of inconsistencies in Customer and Vendor address fields. You will quickly find that SAP will not let you load any address fields unless you get them clean.
Mapping and Conversion Rules.
The documentation of each business object will contain the Data conversion rules (or specification), which include:
* Legacy sources and extraction procedures.
From which Legacy system(s) are we extracting the data and how. Document here specific steps that need to be taken.
What are the cleaning steps to be taken and extraction filters to be used.
Guidelines to apply or rules that is used by many fields (thus avoiding to retype it and making updating easier as it is only in one place).
Which SAP fields to use and how do we get the final value for each SAP field.
General rules are the one that does not yield directly to a field value. For example the way in which we differentiate the material types in the Legacy System is such a rule. Field rules are those that give a value for a specific field.
This is a crucial one. When discussing or writing notes, ALWAYS refer to a field in the form TABLE-FIELD. You will quickly realize that as the project go, different people will start using different names for the same field. As well they may start using the same name for different fields.
On top of this, some fields exist in different views in SAP master data. Sometime it is the same field that is shown at two places while other times it is really two different fields. The best way to know which case apply is to have the TABLE + FIELD information.
In Material Master, the field «Availability check» exists in the “MRP2” and the “Sales Gen” views. If you look at the TABLE-FIELD of each view you get :
Sales Gen : MARC-MTVFP.
In both cases the TABLE-FIELD name is the same, so it is the same field.
In Customer Master, the field ” Terms of Payment’ exist in “Payment Transactions” and “Billing” views. If you look at the TABLE-FIELD of each view you get :
Payment Transactions : KNVV - ZTERM.
Billing Views : KNB1- ZTERM.
It is not the same field. In the payment view, the field is linked to the Company Code while for the Billing view it is linked to the Sales Organization (you find this by looking at the tables keys). So both of these fields can have different values.
Technical Methodology.
A special case for Material Master.
Material Master involves all the domains and may require anywhere from 20 fields to a few hundreds depending on the complexity of your implementation. Some fields will be used by different domains while others will be used by only one domain but its value will have an impact on functionality used by another domain.
This is the most complex Business Object to document and, at the same time, it is the one you must start with in you conversion process.
1st step : Selection of the fields by each domain.
Get each domain with their consultants to go through the mapping file and look at the fields for each material type. The goal here is to see all the fields that are important and ask questions to understand them. This is done separately by each domain and documented in different mapping files. At these points we are not interested about where the values will come from and how will we get them. JUST GET THE MAPPING DONE and work on understanding what material master is. Each time a domain select a field for a specific material type, they must enter their domain type in the list. Here are some (theoretical) examples of mapping from MM, PP and SD.
In Material Master , some fields can be entered / modified in different views. For example, the field “Goods receipt processing time in days (MARC-WEBAZ)” exists in views Purchasing, MRP2 and Quality management. When doing the rules and the load program, the same field can’t be in different views. To solve this, proceed as follow:
See with all implicated domains who are the lead for the field and decide in which view the field should be included.
Taking the example of the field “Goods receipt processing time in days (MARC-WEBAZ)”, it can be decided among the domains to put it in the Purchasing view (and nowhere else).
Material Master Conversion:
High Level Process Design.
These are all the major views involved in Material Master Object:
Basic Data Alternative UOM Inspection Text Classification Sales Organization Sales General Plant Purchasing Foreign Trade Import & Export APO Master Data MRP1 & 2 Quality Management Accounting.
Usually the Function specification Owners will do the recording method to capture all the fields on the above views and prepare the Mapping Logic.
The most complex design involves in Plant merging and Classification Merging . (Refer High Level Process Document)
A member group of the type customer segment group is a collection of users, as defined by the Seller or merchant, who share a common interest.
For Eg: A mining Company has CSG’s like Cerro Matoso( CMSA ),Met Coal ( MTCO ),Base Metals ( BASE ) etc.,
Based on CSG’s the data need to be split up before loading through LSMW for valuation.
The split logic can be done by Loop Component in Business Objects Data Services.
Get the distinct CSG’s in a dataflow. Assign a variable for the sequence number for the max value and loop from the initial.
Other Business Objects Conversion:
For the other BO, because they are simpler than Material Master and involve fewer people, we will start directly with the Conversion rules document. It is in this document that we will both, decide which fields we need and, in a second step, start working on the rules.
Here are some samples of BO conversion rules.
BOM conversion rules sample.
Open Account Receivable conversion rules sample.
Vendor Master conversion rules sample.
Note that SAP term “Security deposit” equal “Retention” in PRMS.
Type of transaction.
TYPE field in PRMS :
Any other type is an error.
Validation to apply both at extraction and load.
Partial PMT………. must be negative in PRMS, if not ERROR.
Credit Memo………must be negative in PRMS, if not ERROR.
Debit Memo……….must be positive in PRMS, if not ERROR.
Any other type is an ERROR.
LSM Load parameters.
KTOPL – Chart of account : CA00.
BUKRS – Company code: 0070.
GSBER – Business Area : 0040.
BUDAT – Posting Date : “05-31-02” or last day of last closed period.
OFFSET – Account (2) : REPRISECL.
SKPERR – Skip err : X.
L egacy S ystem M igration W orkbench (LSMW):
LSMW is used for migrating data from a legacy system to SAP system, or from one SAP system to another.
Apart from standard batch/direct input and recordings, BAPI and IDocs are available as additional import methods for processing the legacy data.
The LSMW comprises the following main steps:
Read data (legacy data in spreadsheet tables and/or sequential files). Convert data (from the source into the target format). Import data (to the database used by the R/3 application.
But, before these steps, you need to perform following steps:
Define source structure: structure of data in the source file. Define target structure: structure of SAP that receives data. Field mapping: Mapping between the source and target structure with conversions, if any. Specify file: location of the source file.
Methods used for data migration like BDC, LSMW and Call Transaction.
All the 3 methods are used to migrate data. Selection of these methods depends on the scenario, amount of data need to transfer. LSMW is a ready tool provided by SAP and you have to follow some 17 steps to migrate master data. While in BDCs Session method is the better choice because of some advantages over call transaction. But call transaction is also very useful to do immediate updation of small amount of data. (In call transaction developer has to handle errors).
SO Bottom line is make choice of these methods based of real time requirements.
These methods are chosen completely based on situation you are in. Direct input method is not available for all scenarios else, they are the simplest ones. In batch input method, you need to do recording for the transaction concerned. Similarly, IDoc, and BAPI are there, and use of these need to be decided based on the requirement.
Try to go through the some material on these four methods, and implement them. You will then have a fair idea about when to use which.
BDC – It is Batch data communication. It’s used for data conversion from legacy system to SAP system. Only technical people can do it. Tcode is SHDB .
LSMW – It is legacy system migration workbench. Its also used for data conversion from legacy system to SAP system. But it is role of functional consultant.
There are 14 steps in LSMW. As soon as you complete the one step, automatically it will go to next step.
In general you can use LSMW. But if you want to transfer more than 40,000 data, then it is not possible in LSMW. That time you can take help of BDC.
LSMW data migration for sales order VA01 / XD01 customer.
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SAP offer free content to help migrate data in SAP (ERP, CRM, etc.). See websmp103.sap-ag. de/rds-dm2erpcrm.
This is indeed a good explaination for data migration process.
Very informative article (probably the best). Keep Posting.
A nice, structured and well written document.
Great piece of literature.
Thanks for sharing the knowledge.
good article Johnpaul !
Wow Johnpaul this is a great article! It’s very informative and goes through a lot of what is required for a successful migration. At Method360 we notice that a lot of people don’t spend the requisite amount of time planning for the migrations and end up having to backtrack and spend a lot of time re-doing things that should have been done much earlier, especially in the data purging and cleansing steps. Clients think that once they get transferred to the newer system that everything will be fixed, but end up with a slow system with a lot of errors. Spending the time to review your historical and master data that may have changed or is no longer necessary can really speed up your systems. In order to help out clients understand everything they need to be successful we created a free workshop. Feel free to give it a look!
What is the difference between data conversion and data migration?
Asked on: May 9th, 2006.
Showing 1 - 1 of 1 Ans Vijayveer Singh.
Answered On : May 24th, 2006.
Data Migration is upgrading from one version to another version fro e. g. from 11.5.9 to 11.5.10.. Data Conversion is receiving data from a legacy system or receiving data from another module ( e. g. PA), validating it and converting it to ur our the target module using the standard import program.
Answered On : May 25th, 2006.
Are there any Migration tools that can make the job easier. What are the steps.
Answered On : Oct 10th, 2006.
Data Conversion refers to the movement of data from a legacy system or application, to a replacement application or sub-system. Data migration refers to movement of data from one database to another database, but not neccesarily to a working application or subsystem tables. Other important terms pertaining to data include;1. Data Cleansing2.Data Integration3.Data replication4. Data Intergrity Testing5.Data Transfer6.Data Transformation7.Data Translation8. Data Partioning.
Answered On : Jan 6th, 2010.
Data Migration is a process of moving required (and most often very large) volumes of data from our clients' existing systems to new systems. Existing systems can be anything from custom-built IT infrastructures to spreadsheets and standalone databases. Data conversion can be defined as a process of converting data from one structural form to another to suit the requirements of the system to which it is migrated. Approach used for Data Conversion:1. Conversion Data Mapping ( map to specify the data of legacy system with data of oracle ERP system ).2. Download Programs ( programs to extract data from database and insert into the Flat file ).3. ASCII Flat File (Flat file / Text file).4. Upload Program5.Interface Tables a) Description of Interface Table. b) Creation of Interface Table.6. Translation Programs7. Interface Programs8. Application Production Table9. Testing10. Write and Perform Conversion Execution Plan. Thanks, Bonthu Nagi Reddy.
Answered On : Jan 29th, 2013.
Informatics Outsourcing is an Offshore Data Management service company. Data Management Service includes all types of Data Conversion, File Conversion, XML Conversion, HTML Conversion, SGML Conversion, Document Conversion, Data Entry, Data Extraction and Validation, OCR and ICR Services with affordable price. Our team to give the solution quickly and given requirements.
Answered On : Aug 26th, 2014.
As an integral part of your team, White Box will provide value throughout the life-cycle of your data management project while minimizing risk. Throughout the process, we are committed to providing your company with superior customer service. Quality control and execution are at the center of everything we do. Here is an illustration to the entire data conversion process: See the illustration below for a step-by-step view of the entire data conversion process.
Answered On : Dec 13th, 2017.
Data conversion is a translation process where data from one format is translated to another so that it can be used in SAP system.
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