# Infosys Whitepaper 
Title: Infosys Test Automation Accelerator 
Author: Infosys Limited 
Format: PDF 1.7 

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 WHITE PAPER HOW TO ENSURE DATA QUALITY   DURING DATA MIGRATION Naju D Mohan, Delivery Manager 

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 Introduction In today’s business world, change is the  only constant and changes make their  appearances in various forms, some of  which are: • Mergers and acquisitions • New compliance requirements • New Package implementations •  Migration to new technologies such as  the cloud • Big data programs Being data driven, the business has to  upgrade and keep its intelligence up- to-date to realize the benefits of these  changes. So in short, all these changes  result in data migrations.  Most of the time, it is assumed that data  migration is an IT problem 2. All the visible  changes and the actions lie with the IT  team, so the business moves on, putting  the entire burden of data migration  management on the IT team.  Mergers and acquisitions and compliance  requirements clearly stand out as having  its origin with the business team. So does  the decision to implement a CRM, loyalty  or HR package with its beginning at the  business department. The need to optimize  operating costs and make intelligent  decisions and act in real-time, leads the  business to migrate to cloud and embark  on big data programs. But the onus of the  migration management, often, lies with the  IT team.<|endoftext|>It must be clearly understood that any data  migration without the business leading the  program has a high rate of failure. Business  has to not just care about data migration  but command it.<|endoftext|>Who is the Primary Owner? According to Gartner, 83% of the  data migration programs fail to meet  expectations, running over time and  budget1.<|endoftext|>Some key reasons for this are: 1.  Poor Understanding About Data  Migration Complexity •   The focus on data migration is lost in  the excitement of the new package  implementation, migration to cloud  or big data initiatives  •   Most often, it is assumed that data fits  one-one into the new system •   The whole attention is on the  implementation of the new business  processes with less or almost no focus  on data migration 2. Lack of Proper Attention to Data •   Lack of data governance and proper  tools for data migration can impact  the quality of data loaded into the  new system •   Mergers and acquisitions can  introduce new data sources and  diverse data formats •   Huge volumes of data may force us  to overlook whether the  data is still  relevant for the business   3. Late Identification of Risks •   Poor data quality of the source  systems and lack of documentation  or inaccurate data models would be  identified late in the migration cycle •   Lack of clarity on the job flows and data  integrity relationship across source  systems would cause data load failures Why Such a High Failure Rate for Data Migration Programs? External Document © 2018 Infosys Limited 

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 An innovative data migration test strategy  is critical to the success of the change  initiatives undertaken by the business. The  test strategy should be prepared in close  collaboration with the business team as  they are a vital stakeholder, who initiated  the change resulting in data migration. The  two principal components which should be  considered as part of the test strategy are: 1. Risk-Based Testing    The data volumes involved in data  migration projects emphasize the  need for risk-based testing to provide  optimum test coverage with the least  risk of failure. Master test strategy  can be created by ensuring proactive  analysis with business and third- parties. Tables can be prioritized and  bucketed based on the business  criticality and sensitivity of data.  Composite key agreed with the  business can be used to select sample  rows for validation in tables with  billions of rows.  2. Data Compliance Testing    It is very important that the quality  assurance (QA) team is aware of the  business requirements that necessitated  data migration, because the change  would have been to meet new  government regulations or compliance  requirements. The test strategy must  have a separate section to validate  the data for meeting all compliance  regulations and standards such as Basel  II, Sarbanes-Oxley (SOX), etc.  Is There a Right Validation  Strategy for Data Migration? A Test Approach Giving Proper Attention to Data Data migration, as mentioned earlier, is  often a by-product of a major initiative  undertaken by the company. So in a  majority of scenarios, there would be an  existing application which was performing  the same functionality. It is suitable to  adopt a parallel testing approach which  would save effort spent to understand  the system functionality. The testing can  be done in parallel with development in  sprints, following an agile approach to  avoid the risk of failure at the last moment.<|endoftext|>1. Metadata Validation    Data migration testing considers  information that describes the location  of each source such as the database  name, filename, table name, field or  column name, and the characteristics  of each column, such as its length and  type, etc. as part of metadata. Metadata  validation must be done before the  actual data content is validated, which  helps in early identification of defects  which could be repeated across several  rows of data.<|endoftext|>2. Data Reconcilliation    Use automated data comparison  techniques and tools for column to  column data comparison. There could  be duplicate data in legacy systems  and it has to be validated that this is  merged and exists as a single entity  in the migrated system. Sometimes  the destination data stores do not  support the data types from the source  and hence the storage of data in such  columns have to be validated for  truncation and precision. There could  be new fields in the destination data  store and it has to be validated that  these fields are filled with values as per  the business rule for the entity.<|endoftext|>Benefits  A well thought-out data migration validation strategy helps to make the data migration  highly predictable and paves the way for a first-time right release. Regular business  involvement helps to maintain the testing focus on critical business requirements. A  successful implementation of the shift-left approach in the migration test strategy helps  identify defects early and save cost.<|endoftext|>External Document © 2018 Infosys Limited 

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 Case Study: Re-Platforming of Existing HP NEOVIEW Data Warehouse to Teradata The Client   One of the largest super market chains in  the United Kingdom which offers online  shopping, DVD rentals, financial services,  and multiple store locations.<|endoftext|>The Objectives •  To complete the re-platform of HP  Neoview to Teradata and re-platform  associated services before HP  discontinued support to Neoview  •  To migrate the existing IT business  services currently operating against a  Neoview data warehouse onto a Teradata  warehouse with minimal disruption •  To improve the performance of  current  Ab-Initio ETL batch processes and  reporting services using Microstrategy,  SAS, Pentaho, and Touchpoint  The QA Solution The validation strategy was devised  to ensure that the project delivered a  like-for-like, ‘lift-and-shift’. This project  had environmental challenges and  dependencies throughout the entire  execution cycle. SIT phase overcame all  the challenges by devising strategies  that departed from traditional testing  approach in terms of flexibility and  agility. The testing team maintained close  collaboration with the development and  infrastructure teams while maintaining  their independent reporting structure.  The approach was to maximize defect  capture within the constraints placed on  test execution.<|endoftext|>It was planned to have individual  tracks tested independently on static  environment and then have an end- to-end SIT, where all the applications /  tracks are integrated. Testing was always  focused on migrating key business  functions on priority such as sales  transaction management, merchandise  and range planning, demand  management, inventory management,  price and promotion management, etc.<|endoftext|>The Benefits •  15% reduction in effort through  automation using in-house tools •  100% satisfaction in test output  through flexibility and transparency  in every testing activity achieved  through statistical models to define  acceptance baseline End Notes 1. Gartner, “Risks and Challenges in Data Migrations and Conversions,” February 2009 2. https://www.hds.com/go/cost-efficiency/pdf/white-paper-reducing-costs-and-risks-for-data-migrations.pdf © 2018 Infosys Limited, Bengaluru, India. All Rights Reserved. Infosys believes the information in this document is accurate as of its publication date; such information is subject to change without notice. Infosys  acknowledges the proprietary rights of other companies to the trademarks, product names and such other intellectual property rights mentioned in this document