Transcript Data Conversion Methodology Summary

Data Methodology
Camille C. Alvarez
December 6, 2010
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Agenda
What is Data Conversion?
Data Conversion Methodology
Data Conversion Sequence
Data Methodology Controls
Data Wrap Up
Questions
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What is Data Conversion?
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What is Data Conversion
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Data Conversion Objects

Master Data – a collection of information about a person or an object, e.g. a cost object,
vendor, or G/L account. Generally for end users, master data is reference data that you
will look up and use, but not create or change
 For example, a vendor master record contains not only general information such as the
vendor's name and address, but also specific information, such as payment terms and
delivery instructions.

Transactional Data - data related to a single business event such as a purchase
requisition or a request for payment.
 For example, when you create a requisition, ERP creates an electronic document for that
particular transaction. SAP gives the transaction a document number and adds the
document to the transaction data that is already in the system.

Historical Data - Data from previous time periods, in contrast to current data. Historical
data is used for trend analysis and for comparisons to previous periods.
 We will not be loading any historical data (except for monthly GL Balances).
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Data Methodology and Process
And
Controls
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Deployment Activities
Process Overview
Prepare
Country
“Self
Preparation”
Preliminary
Assessment
Vendor
Engagement
Knowledge
Transfer
Deployment
Set-Up
Deliver
Maintain
PROJECT MANAGEMENT
DESIGN
(Fit/Gap)
BUILD
TEST
DEPLOY
SUPPORT
User Support
&
Application
Maintenance
DATA Migration
CHANGE MANAGEMENT
6-7 months
1 month
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Organization Structure
Data Methodology
Core Technical Team
Core Functional Team
•Finance
•Procure to Pay
•Supply Chain Execution
•Order To Cash
•Application Development
•Data Conversion
•Data Cutover
•Infrastructure
•Quality Assurance
•Support
Wave/Deployment
Team
•Local Business
Country
•System Integrators
Project Management Office
Change Enablement
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Core Data Conversion
Technical Team
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Data Methodology Framework
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Data Migration Activities
Content
Content
Process
 Data Cleansing
- Data Cleansing Guidelines
- Data Cleansing Execution and Validation
 Data Mapping
-
DATA
MANAGEMENT
(cross)
Static / Dynamic objects list
Data Source list
Functional And Technical Data Mapping – Data transformation rules
Conversion Strategy (Manual vs. Automatic - Historical depth)
Data Migration Realization Plan
 Data Migration Realization
-
Legacy data extraction and transformation
Data Construction
Data Conversion tools Enhancement / Realization
Data Conversion tools Unit Test
 Data Conversion Mock Testing
- Mock 1 Data Conversions
- Mock 2 (UAT) Data Conversion
 Data Conversion during Deploy Stage
-
Data Conversion Plan Finalization
Go-Live Simulations
Data Conversion Productive Run
Data Validation and Sign-Off from Business Users
 Data bugs fixing [during SUPPORT]
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Data Cleansing
Preparation/Fit Gap/Build Phase
 In order to have proper data to be extracted, transformed and uploaded it
will be necessary to perform a Cleansing Activity
Data Cleansing
Preparation
 During the Preparation Stage the Data Cleansing Activity have to be
launched. A Specific Document prepared by the Enterprise Data
Management Office, that explain the rationales to be used to cleanse the
main master data, will be distributed to the LPO within the Wave
Communication Package.
 The Business will be requested to prepare the metrics of the cleansing
activities that have to be performed.
 In the context of the preliminary Assessment specific Data Cleansing
Sessions will be scheduled, in order to clarify any doubt related to the
cleansing activities and to agree a cleansing plan.
Data Cleansing
Execution
 The cleansing Activities that can be performed on Impulse will be launched
immediately. The Data that can’t be cleansed in legacy will need to be
identified, tracked and treated during the input files preparation. This
activity have to be performed before the end of the Build Phase
Data Cleansing
Validation
 After the Data Cleansing Execution the Data Cleansing Metrics Have to be
finalized and validated by the Enterprise Data Management Office.
Validated Data can be used to prepare Mock testing
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Data Mapping
Fit Gap / Build Phase
 The first Mapping activity that will be conducted is the Data Object
Mapping. The actual list of data object, provided by the Core Data
Conversion Team, is analyzed by SI and LPO, in order to identify any
possible Gaps.
 For Each object it will be necessary to assess the Data Source
Data Object
Mapping
 For Each Object it will be necessary to assign a business responsible that
will be the primary contact for the SI for all the Data activities that concern
this object
 For each object it will be necessary to define the data conversion strategy
(Manual versus Automatic, Conversion Tier)
 Each difference between the actual list and the analysis will be submitted
for approval to Core Data Conversion Team
Functional Data
Mapping
Technical Data
Mapping
 For each data migration object, a field functional data mapping must be
performed. An ERP Field list will be provided by the Core Data Conversion
Team. The Legacy reference for this field (Source, field description, Screen
name and Screen field name) must be identified and indicated
 For all Legacy fields indicated it will be necessary to indicate Legacy field
and table name, field format and length, in order to identify any possible
inconsistency between source and destination
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Data Migration Realization
Build Phase
Data Conversion
Tools
Enhancement
Data Construction
Preparation
Data Conversion
Unit Test
 Following the results of the data Mapping, the Core technical team will
upgrade the data conversion tools
 As Well, the Core Data Conversion Team will provide to the Local Business
the guideline to prepare the “Data Construction” files. A first example of
these DC files needs to be provided early to perform the Data Conversion
Tools Unit test. Local Business will be supported by the development team
in preparing these files
 After the data conversion tools enhancement, Unit test of Extraction,
transformation and Upload needs to be performed.
 The Upload test will be performed in the development environment, in a
dedicated client.
 Deployment team can be requested to support the validation of these test
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Data Conversion Mock Testing
Testing Phase
 As soon as the Test Environment will be available the Mock Test 1 will be
launched. After the Environment preparation, the manual configuration
execution and validation, the Core Data Conversion Team will perform a
data conversion test.
Mock Conversion
1
 Likely the scope of this conversion will be the totality of the static data and
anticipate the production volume of the Transactional Data
 These Conversions will be validated following the guidelines described in
appendix 2
 This Conversion test will be tracked on defect system such as HPQC
 The Mitigation plan for the defects will establish Roles and Responsibility
of the involved functions
Mock Conversion
2
 After the execution of the mitigation plan for the defect raised during Mock
1 a second Mock will be executed with the same principle already
described for the Mock 1
 This second mock must be scheduled in order to be able to use Mock 2
converted data for IST2
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Data Migration Productive Run
Deploy / Support Phase
 Within the Cutover Plan, a detailed Data Conversion Plan needs to be
produced. This Plan needs to detail the Conversion Sequences, the
Manual Conversion Scheduling and the data validation.
Data Conversion
Plan
 Conversion Schedule, Conversion execution responsible and Data
Validation Responsible needs to be indicated.
 Final Legacy Extracts, Data freezing schedule and Dual Maintenance
Rules needs to be finalized and approved
Mock Conversion
3 (Go Live
Simulation)
 The Final Data Conversion Plan will be tested within the Go-Live
Simulation. The procedure for the data conversion preparation, execution
and validation are the same already indicated for Mock 2
Data Conversion
Productive Run
 After the Go Decision, the cutover execution happen. Within the cutover
execution there’s the data migration productive run, that will follow the final
data conversion plan and will be submitted to the same validation process
as the Go Live Simulation.
 After the productive run, the Enterprise Data Migration Office will starts the
Data Quality enhancement
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Data Conversion Sequence
Diagram
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Data Methodology Controls
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Data Wrap Up
Data Methodology provides the following:
– Follows and supports the SDLC
– Promotes execution and an engagement model
 Wave, Core, and local business
– Sets expectations and support data conversion
activities
– Establishes deliverables and metrics
– Roles and Responsibilities are established in each of
their data activity phase for accountability,
consultation, or information
– Provides a process guideline for policies and
procedures controls for audit purposes
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Questions
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Thank you!!!
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References
Detail to Data Migration Methodology.
–
http://im-insideworld/is/isprivate/projectshome/IMGlobalPrivateprojwksp/Project%20Documents/Deployment%20
Methodology/IMG_CP_Data%20Migration%20Methodology.pptx
Data Conversion Controls for Awareness
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