My presentation to SAP's UK #SAPForum in Birmingham on July 03 2013. Synopsis: 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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Data Design:
The X Factor for a Successful SAP Migration
Richard Neale
Product & Marketing Manager
June 2013

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ENTOTA Customers
Unrivalled SAP Information Management Expertise
Consumer Goods: SAP Data Migration
Strategy & Deployment, Application
Integration
Retail: SAP Data Migration,
Governance
Consumer Goods: SAP Data
Migration Reconciliation
Media: Business
Intelligence
Advertising: SAP Data
Migration Strategy &
Deployment
Banking: Financial Consolidation
and Reporting
Financial Services:
Business Intelligence
Strategy
Consumer Goods: SAP Data
Migration, SAP Application
Integration, Strategy
Utilities: SAP Data
Migration
Healthcare: SAP Data
Migration Best Practice
Insurance: Business
Intelligence, Governance, Data
Quality
Hi-tech: SAP Data Migration, Application
Integration, Data Quality, Strategy
Insurance
Services: SAP
Data Migration
Foods: SAP Data Migration post
acquisition
And more…

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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
80% of organizations… will underestimate the costs
related to the data acquisition tasks by an average of
50 percent”
Gartner

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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

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“My implementation partner is doing the migration”

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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

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How you approach your migration depends on complexity and appetite for risk
Good ‘data design’ underpins success
Governance & Data Design Effort
Low High
Level 1: Excel, LSMW ‘True Data
Position Known at Go-Live’
Data
Confidence
Level
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

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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

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Data Design + Source = Conversion Objects
Legacy Source #1 Target Data Design
High Quality, Complete
Data
in SAP System
Data Conversion
Inventory
Legacy Source #2
Legacy Source #3

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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

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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

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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

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Data Designers

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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

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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

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Accelerate
These definitions drive the auto-generation of the
data migration, validation and reconciliation jobs

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Reuse

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Data Migrators and ETL Specialists

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Benefit enormously from the data design

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ENTOTA Data Migration Portal

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Data Migration code generated directly from Data Design
Ability to execute segments independently
Consistent approach for all objects

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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.

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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

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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

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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

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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

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Project and Programme Managers

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Project Control
Pre-Defined Project Management Metrics & Reporting
Project Metrics:
 By Role
 By Process
 By Data Object
 By Status
 Manage by Fact

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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

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Progress Status
At a glance project status shows what’s on track and what isn’t

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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

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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

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An invitation
Visit our stand P7 during the coffee break and drinks reception later today
Investigate the suitability of a SAP Data Migration Workshop with ENTOTA where we will
cover…
 The importance of Target Data Design to successful migration
 How to effectively collaborate on Data Design
 Selecting the optimal approach to your data migration
 Techniques to reduce risks, timescales and costs through automated code generation
 Tools to track and manage your SAP Data Migration projects
 Using target data design as a foundation for Data Governance initiatives

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Stay in contact
www.entota.com
www.linkedin.com/company/entota
twitter.com/#!/ENTOTA
www.youtube.com/user/ENTOTA

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Thank You
Richard Neale
Product and Marketing Manager
richard.neale@entota.com
@richard_neale