Deciding on migration related setups. Legacy data fields could have been misused (holding information different from what this field was initially intended to be used for). Developing guidelines for use during manual migrations, which show how to determine missing values while entering the data. Functional subtleties related to the co-mingling of migrated data and data created in the destination system may be difficult to identify early in the migration process. 0000007022 00000 n
These risks should become the basis for the data migration testing strategy. The mere act of migrating one solitary piece of software is already difficult in itself. Verify the appropriate level of experience for each team member and train as required on data migration principles, the source and the destination system. 0000001672 00000 n
Data Cutover
This is the final Data Migration into the SAP production System. Data Migration Checklist: The Definitive Guide to Planning Your Next Data Migration Coming up with a data migration checklist for your data migration project is one of the most challenging tasks, particularly for the uninitiated.. To help you, we've compiled a list of 'must-do' activities below that have been found to be essential to successful data migration planning activities. Derive priorities and business rules for data cleansing. To start, look at your migration project more strategically, and take the opportunity to improve your content along the way. Getting everyone on the same page is critical, since IT needs to be aware of the strategic goals of your migration project, and business leaders must be mindful of the tactical and operational challenges associated with a project of this scale. Create your project plan to minimize the risks of your software migration process.You may also see scope management plans, 15+ Project Plan Templates in Word | Excel | Google Docs | Apple Pages | Google Sheets | Apple Numbers -. This approach tends to identify application errors with data that has been migrated as designed. Data Cleansing
Before data can be successfully migrated it data needs to be clean, data cleansing is therefore an important element of any data migration activity:
Data needs to be in a consistent, standardised and correctly formatted to allow successful migration into SAP (e.g. Data Migration Testing Strategy: A Complete Guide to Data Migration Testing Success, Creating a Data Quality Rules Management Repository, Data Migration Best Practices for your Next Project, 8 Tips for Becoming a Better Data Migration Client, How to avoid a data migration traffic-jam, 6 tips for ‘selling’ a best-practice data migration. For planning purposes, consider the time to verify that the migration process was completed successfully. Otherwise, the whole process may go south, irregardless of how much you prepared for it.You may also see feasibility report examples. The data that your present system or software holds is what we would consider accurate. ‘Open’ Transactional data (e.g. For example Business Partner.Field DescriptionMandatoryField Description, for example Customer NameTable/StructureMandatorySAP Table Name.Field NameMandatorySAP Field NameLengthMandatoryLength of fieldFormatMandatoryExample CHAR, DATS, CURRField StatusMandatoryField Status; R=Required, A=Automatic, C=Conditional,
O=Optional, NR=Not RequiredCommentsMandatoryInsert comments to assist with data mapping and transforming. Focus on the areas where you will see an immediate business and operational impact, and then structure your Data Migration strategy accordingly. Roles and Responsibilities
The successful migration of data into SAP requires a significant and diverse input from many different sources. The facility also caters for ‘data transformation’ where field values can be created from simple predefined logic. This analysis will derive data enrichment to fill in incomplete records, identify data cleansing requirements through pre-migration analysis, dry runs the migration process and verify the results sting before understanding the final data migration requirements. It’s not necessary to transfer each one, only those that are relevant and up to date. %PDF-1.4
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Create strategy for field mappings and data build where appropriate. Create a retirement plan to assess if the data is no longer required, thus making it unnecessary to the transfer. Configuration Data
This is data that is set up on SAP during the build and configuration process as it is configured. The responsibilities of each data entity “team” can be shared in whatever way suits them best but the likely division is shown below. ¢ üA ’ K9 •u �’ !„ %„ @ �’ �’ K9 õk õk ဠဠ@ `9 *œ *œ *œ �’ Ä õk ¸ ဠEu 8 ဠ%9 *œ �’ %9 *œ *œ – s r ˜ }u ဠÿÿÿÿ àsKåUÎ ¹u T“ ¬ s € 9 v9 0 ¦9 ó �C ” �C Ø " 1 �C •u I È Õ� u� r *œ ç� \ C‘ M Õ� Õ� Õ� K9 K9 › Õ� Õ� Õ� ¦9 �’ �’ �’ �’ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ ÿÿÿÿ �C Õ� Õ� Õ� Õ� Õ� Õ� Õ� Õ� Õ� ²^ »j :
Table of Contents TOC \o "1-4" \h \z \u
HYPERLINK \l "_Toc188270504" 1 Document Information PAGEREF _Toc188270504 \h 4
HYPERLINK \l "_Toc188270505" 2 Introduction PAGEREF _Toc188270505 \h 5
HYPERLINK \l "_Toc188270506" 3 Definitions of Different Types of Data PAGEREF _Toc188270506 \h 6
HYPERLINK \l "_Toc188270507" 3.1 Master Data PAGEREF _Toc188270507 \h 6
HYPERLINK \l "_Toc188270508" 3.2 Configuration Data PAGEREF _Toc188270508 \h 6
HYPERLINK \l "_Toc188270509" 3.3 Transaction Data PAGEREF _Toc188270509 \h 6
HYPERLINK \l "_Toc188270510" 4 Data Migration Activities PAGEREF _Toc188270510 \h 7
HYPERLINK \l "_Toc188270511" 4.1 Define the SAP Data Requirements (Functional) PAGEREF _Toc188270511 \h 7
HYPERLINK \l "_Toc188270512" 4.2 Define the SAP Data Requirements (Technical) PAGEREF _Toc188270512 \h 7
HYPERLINK \l "_Toc188270513" 4.3 Identify the Legacy Data (Functional) PAGEREF _Toc188270513 \h 7
HYPERLINK \l "_Toc188270514" 4.4 Identify the Legacy Data (Technical) PAGEREF _Toc188270514 \h 7
HYPERLINK \l "_Toc188270515" 4.5 Define Data Standards PAGEREF _Toc188270515 \h 7
HYPERLINK \l "_Toc188270516" 4.6 Legacy Data Cleansing PAGEREF _Toc188270516 \h 7
HYPERLINK \l "_Toc188270517" 4.7 Determine the Data Transfer Method PAGEREF _Toc188270517 \h 7
HYPERLINK \l "_Toc188270518" 4.8 Data Mapping and Transformation PAGEREF _Toc188270518 \h 8
HYPERLINK \l "_Toc188270519" 4.9 Identify Missing Data PAGEREF _Toc188270519 \h 8
HYPERLINK \l "_Toc188270520" 4.10 Resolve Missing Data PAGEREF _Toc188270520 \h 8
HYPERLINK \l "_Toc188270521" 4.11 Extract Legacy Data PAGEREF _Toc188270521 \h 8
HYPERLINK \l "_Toc188270522" 4.12 Design Automatic Loads PAGEREF _Toc188270522 \h 8
HYPERLINK \l "_Toc188270523" 4.13 Develop Automatic Loads PAGEREF _Toc188270523 \h 8
HYPERLINK \l "_Toc188270524" 4.14 Manual Data Entry PAGEREF _Toc188270524 \h 9
HYPERLINK \l "_Toc188270525" 4.15 Data Loading Instructions PAGEREF _Toc188270525 \h 9
HYPERLINK \l "_Toc188270526" 4.16 Trial Data Upload - Running PAGEREF _Toc188270526 \h 9
HYPERLINK \l "_Toc188270527" 4.17 Trial Data Upload - Checking PAGEREF _Toc188270527 \h 9
HYPERLINK \l "_Toc188270528" 4.18 Execution Plan for Final Uploads PAGEREF _Toc188270528 \h 9
HYPERLINK \l "_Toc188270529" 4.19 Dual Data Maintenance PAGEREF _Toc188270529 \h 9
HYPERLINK \l "_Toc188270530" 4.20 Data Cutover PAGEREF _Toc188270530 \h 9
HYPERLINK \l "_Toc188270531" 4.21 Reconcile the Migrated Data PAGEREF _Toc188270531 \h 9
HYPERLINK \l "_Toc188270532" 4.22 Data Sign-off PAGEREF _Toc188270532 \h 9
HYPERLINK \l "_Toc188270533" 5 Data Migration Guiding Principles PAGEREF _Toc188270533 \h 10
HYPERLINK \l "_Toc188270534" 5.1 Data Migration Approach PAGEREF _Toc188270534 \h 10
HYPERLINK \l "_Toc188270535" 5.1.1 Master Data - (e.g. Please add your details by clicking on the button below, complete the form, and our editorial team will reach out to you with further details. Look closely at the ROI of automated testing if there is some concern about the costs, time commitment or the iterative nature of migration verification via sampling. Instead of just focusing on the basics, you’ll take steps to uncover information of business value, decrease organizational risk, and improve the overall findability and usability of your documents. Highlight any data gaps from legacy systems. Getting all your teams on the same page will help you develop a clear plan, and will eliminate any disconnect between their expectations. Deciding on migration related setups. The advantages of this approach are;
Avoids the duplication of data throughout the system landscape. Data Migration Methods
There are four primary methods of transferring data from a legacy system into SAP. First of all, your team needs to assign a leader who has the ability to effectively oversee the whole project. Getting everyone aligned will help your organization develop a clear migration strategy that considers all the stakeholders and business units involved. Data cleansing is typically a business activity. The data cleansing cycle includes the following steps:
The elimination obsolete records. There will be at least one trial cutover.. For complex, high-risk, migrations several trial runs may be performed, until the result is entirely satisfactory and 100% correct. This is to minimize the errors and risks that occur as a result of migration and to perform the migration … In the first case, the financial services industry has evolved to the point where data interchange standards exist, which simplifies this process greatly. His thorough understanding of the supported platforms, user interface design and novel testing techniques directly resulted in Valiance’s unique product direction path. Va`N��,�!J �}n#
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