Data Design - the x factor for a successful data migration v1.3


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My presentation to SAP's UK #SAPForum in Birmingham on July 03 2013.

Because data is what drives key business processes, to fully realise return on your SAP investment it's critical that the data you have is of high quality and validated to fully support your business processes. Although most data migrations focus almost exclusively on the technical build the 'X factor' for success lies in good Data Design. This session will explain how to select the optimal migration approach for your requirements, what Data Design actually involves and how collaborating with the business in Data Design will dramatically reduce project risks, timescales and costs.

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  • SynopsisData Design: The X Factor for a Successful SAP MigrationThe biggest mistake most organisations make is to approach data migration as a tactical challenge, overlooking the fact that data is what drives their key business processes. Data Migration can be expensive, risky and difficult – yet in spite of well-known risks many businesses frequently do not fully understand the challenges until too late and problems become expensive to fix.  Sharing ‘real world client experiences this session discuss:Why good Data Design is critical to successful data migrationHow to engage the business to ensure the data you have is transformed into the data your business processes needHow to select the optimal approach for your specific data migration requirementsHow automated code generation dramatically reduces project risks, timescales and costsAlthough based on Clive’s extensive SAP experience there are lessons to be learned here for all enterprise scale data migrations.
  • Within the Data Migration area, again the reports provide validation and information to support the creation of the mapping specifications and value mapping processes, as well as tracking progress for the projects management team. The actual data flowing through the migration process is dynamically available within the Data Profiling, Rule Violation and Data Model reports.
  • Data Design - the x factor for a successful data migration v1.3

    1. 1. ENTOTA 2013© Data Design: The X Factor for a Successful SAP Migration Richard Neale Product & Marketing Manager June 2013
    2. 2. © 2011 ENTOTA LTD 33ENTOTA 2013© Data Migrations often get a bad press More than 80% of data migration projects run over time and/or over budget. Cost overruns average 30%. Time overruns average 41% Bloor
    3. 3. © 2011 ENTOTA LTD 44ENTOTA 2013© Data Migrations often get a bad press 80% of organizations… will underestimate the costs related to the data acquisition tasks by an average of 50 percent” Gartner
    4. 4. © 2011 ENTOTA LTD 55ENTOTA 2013© Why do so many data migrations fail? Attitude to the data migration project • Tactical • One-off • Outsourced, 3rd parties Technical and Data issues • Source data quality and knowledge • Continuously changing target • Too many others to list here! Management issues • Lack of visibility into progress and status leads to nasty surprises • Politics, culture and deadlines Issues caused by spreadsheets and lack of collaboration
    5. 5. © 2011 ENTOTA LTD 66ENTOTA 2013© “My implementation partner is doing the migration”
    6. 6. © 2011 ENTOTA LTD 77ENTOTA 2013© Is Excel Appropriate to Manage Complexity? Customer example… Finance & Sales 16 Data Objects 20 Legacy sources 280+ Mapping Specs 100+ Users involved in DM process design, build, review, sign-off
    7. 7. © 2011 ENTOTA LTD 88ENTOTA 2013© How you approach your migration depends on complexity and appetite for risk Good ‘data design’ underpins success Governance & Data Design EffortLow High Level 1: Excel, LSMW ‘True Data Position Known at Go-Live’ DataConfidenceLevel Low High Traditional Approaches Level 3: SAP DM Best Practice Plus ‘Business Process Valid and Repeatable’ Business Process Validity Data Uncertainty Risk Post Go-Live Data Quality Level 2: SAP DM Best Practice ‘Technically Valid Data’ Level 4: DM with Governance ‘Business Process Valid, Repeatable, Post Go-Live Data Quality and Governance’ With Data Design and the ENTOTA DM Portal
    8. 8. © 2011 ENTOTA LTD 99ENTOTA 2013© DM Readiness Project Prep Extract, Stage, Clean Extract & Stage Active Records, Cleanse, De- dupe Business Blueprint Final Prep Realisation Target Data Design Data Object Inventory, Definitions, Validation, Business Rules Execute Build Technical Build, Data Conversion Design, SAP Config Extracts, Mappings Migrate & Reconcile Value Mapping, Iterative Load Simulations, Execute Load Cycles, Reconcile Go-Live Sign-Off, Remediation,, Ongoing Quality Profile Legacy Assess quality & risk, archiving Decision 1: How to manage Data Design Detailed & communicated understanding of what data SAP needs to run optimally Decision 2: What technology to Execute Build Building a technical solution which exactly reflects Data Design SAP Data Migration Process Transforming the data you have into the data your new business processes need
    9. 9. © 2011 ENTOTA LTD 1010ENTOTA 2013© Data Design + Source = Conversion Objects Legacy Source #1 Target Data Design High Quality, Complete Data in SAP System Data Conversion Inventory
    10. 10. © 2011 ENTOTA LTD 1111ENTOTA 2013© Data Design + Source = Conversion Objects Target Data Design High Quality, Complete Data in SAP System Data Conversion Inventory Legacy Source #2
    11. 11. © 2011 ENTOTA LTD 1212ENTOTA 2013© Data Design + Source = Conversion Objects Target Data Design High Quality, Complete Data in SAP System Data Conversion Inventory Legacy Source #3
    12. 12. © 2011 ENTOTA LTD 1313ENTOTA 2013© Data Design = Template for Execution Ensuring that the migrated data is what SAP needs to run smoothly Time spent on Data Design will...  Reduce scrap & rework  Avoid wasted test cycles and cost  Improve data quality  Lower the cost and risk of future migration  Support post go-live data governance Today Should be Time Spent on Data Migration Data Design Execute Build Load
    13. 13. © 2011 ENTOTA LTD 1414ENTOTA 2013© Data Design Needs to be Collaborative One version of the truth regardless of role People who Manage the project and programme • Key Stakeholders, Programme & Project Managers • Project Governance and sign-off • Manage Risk People who do Data Design • Business Users, Functional Consultants, SME’s, Data Architects • Define Data Requirements for Target SAP Application • Data Definitions, Business & Data Quality Rules People who transform & migrate data into SAP • Data Migration Team, ETL Developers, ABAP & LSMW Developers • Build Technical Solution to Deliver Against Data Design • Data Migration, Data Quality, Application Integration Manage Project Data Design Execute Data Design M D E Data Design
    14. 14. © 2011 ENTOTA LTD 1515ENTOTA 2013© Key Project Management Features:  Project management metrics enabling management by ‘fact’  Project Status categories  Audit trail Key Data Design Features:  Web based, version controlled, secure environment for Data Design available for project usage or ongoing governance  Pre-defined business process names as defined in SAP  Pre-defined data object inventory & associated data definitions to jump start projects Key Execution Features:  Full SAP Data Migration methodology and project controls built in  SAP Data Services auto-generation engine builds end-to-end SAP Data Services jobs dramatically reducing build costs  Automated Mapping Specification driven from data design ENTOTA Data Migration Portal One version of the truth regardless of role Manage Project Data Design Data Migrators M D E Data Migration Portal
    15. 15. ENTOTA 2013© 16 Data Designers
    16. 16. © 2011 ENTOTA LTD 1717ENTOTA 2013© Data Designers should… Organise  Assign business process names  Assign business process owners  Create the data object inventory Define  For each data object • Define the data quality rules to setup the data quality ‘firewall’ • Business rules that define what is business valid • Active record determination and archiving rules Map  Centrally maintained mapping rules integrated with sample records  Structured approach to source-to-target mapping rules enables reusability
    17. 17. © 2011 ENTOTA LTD 1818ENTOTA 2013© Data Design drives successful migrations Manage Inventory  Conversion inventory defines the scope of the migration  Ensures a centralised record of all the data related activities that need to take place at cutover Collect  Often need to provide data inputs when data not held within a source system  ENTOTA recommend a single place to collect user specified data rather than spreadsheets that have little control or governance Synchronise  Single place to manage everything ensures nothing is out of sync  Target system interrogated to ensure technical and business validity  Auto-generated code always based on the latest definitions
    18. 18. © 2011 ENTOTA LTD 1919ENTOTA 2013© Accelerate These definitions drive the auto-generation of the data migration, validation and reconciliation jobs
    19. 19. © 2011 ENTOTA LTD 2020ENTOTA 2013© Reuse
    20. 20. ENTOTA 2013© 21 Data Migrators and ETL Specialists
    21. 21. © 2011 ENTOTA LTD 2222ENTOTA 2013© ENTOTA Data Migration Portal
    22. 22. © 2011 ENTOTA LTD 2323ENTOTA 2013© Data Migration code generated directly from Data Design Ability to execute segments independently Consistent approach for all objects
    23. 23. © 2011 ENTOTA LTD 2424ENTOTA 2013© Sample Record Identification Sample Record Identification • Pre-built code to handle the selection of records for test execution cycles. • Ability to switch test filtering on and off with no change to the ETL code. • Test data controlled from Portal by Business or DM Team.
    24. 24. © 2011 ENTOTA LTD 2525ENTOTA 2013© Technical Validation Technical Validation • Pre-built code to validate the mandatory columns, data format and lookup values. • Handles date, varchar, decimal and time • Driven from Data Definition in the ENTOTA DM Portal
    25. 25. © 2011 ENTOTA LTD 2626ENTOTA 2013© Business Enrichment and Validation Business Enrichment • Application of rules defined in the Portal • Application of value mappings and default values • Validates field population and allows for remediation
    26. 26. © 2011 ENTOTA LTD 2727ENTOTA 2013© Rule Violation Processing Rule Violation Processing • Standardised approach to error resolution and reporting • Provides additional metadata to resolve issues effectively • All errors reported in a single reporting table
    27. 27. © 2011 ENTOTA LTD 2828ENTOTA 2013© Reconciliation Reconciliation • Pre-built reconciliation to facilitate business data sign off • Provides information on failed records which have not loaded and also individual field reconciliation for data records that have
    28. 28. ENTOTA 2013© 29 Project and Programme Managers
    29. 29. © 2011 ENTOTA LTD 3030ENTOTA 2013© Project Control Pre-Defined Project Management Metrics & Reporting Project Metrics:  By Role  By Process  By Data Object  By Status  Manage by Fact
    30. 30. © 2011 ENTOTA LTD 3131ENTOTA 2013© Active Record Determination ENTOTA Reporting Metrics are gathered for all aspects of the Data Migration Mapping Specification Progress Status Profiling reports show the state of the source data and provide the first indication of any challenges ahead
    31. 31. © 2011 ENTOTA LTD 3232ENTOTA 2013© Progress Status At a glance project status shows what’s on track and what isn’t
    32. 32. © 2011 ENTOTA LTD 3333ENTOTA 2013© ROI driven by good data design ROI model for a 2 source, 35 business object single SAP data migration over 180 days Estimated FTE saving of 4 with associated cost saving
    33. 33. © 2011 ENTOTA LTD 3434ENTOTA 2013© Summary Good Data Design is critical to successful data migration  Based on the target, not the source  No hardcoded source-to-target mappings  Design separated from execution Business and IT (and the implementation partner) must collaborate to ensure the data you have is transformed into the data your business processes need Automated ETL code generation based on data design and best practice dramatically reduces project risks, timescales and costs Target Data Design ensures re-use across multiple migration projects Data Design provides a foundation for ongoing data governance after go-live
    34. 34. © 2011 ENTOTA LTD 3535ENTOTA 2013© Stay in contact!/ENTOTA
    35. 35. T +44 (0)845 003 8304 E W Thank You Richard Neale Product and Marketing Manager @richard_neale