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Data Methodology

Camille C. AlvarezDecember 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

Country“Self

Preparation”

PreliminaryAssessment

VendorEngagement

KnowledgeTransfer

Prepare

DESIGN(Fit/Gap)

BUILD TEST DEPLOY

Deliver

SUPPORT

PROJECT MANAGEMENT

CHANGE MANAGEMENT

User Support&

ApplicationMaintenance

User Support&

ApplicationMaintenance

Maintain

DATA Migration

DeploymentSet-Up

6-7 months 1 month

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Organization Structure Data Methodology

Core Technical Team

• Application Development

• Data Conversion• Data Cutover• Infrastructure

• Quality Assurance• Support

Core Functional Team

• Finance• Procure to Pay• Supply Chain

Execution• Order To Cash

Project Management Office

Wave/Deployment Team

• Local Business Country

• System Integrators

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

ContentProcess Content

DATA MANAGEMENT

(cross)

Data Cleansing - Data Cleansing Guidelines- Data Cleansing Execution and Validation

Data Mapping- 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 CleansingPreparation/Fit Gap/Build Phase

Data Cleansing Preparation

In order to have proper data to be extracted, transformed and uploaded it will be necessary to perform a Cleansing Activity

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 MappingFit Gap / Build Phase

Data Object Mapping

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

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

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

Technical Data Mapping

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 RealizationBuild Phase

Data Conversion Tools

Enhancement

Following the results of the data Mapping, the Core technical team will upgrade the data conversion tools

Data Construction Preparation

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

Data Conversion Unit Test

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 TestingTesting Phase

Mock Conversion 1

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.

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 RunDeploy / Support Phase

Data Conversion Plan

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.

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 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

Data Wrap Up

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Questions

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Thank you!!!

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Detail to Data Migration Methodology.– http://im-inside-world/is/isprivate/projectshome/IMGlobalPrivateprojwksp/Project%20Documents/D

eployment%20Methodology/IMG_CP_Data%20Migration%20Methodology.pptx

Data Conversion Controls for Awareness

References

Data Conversion Policy and Procedures

Data Conversion RACM

Data Conversion Key Controls

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