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Migrating data: How
to reduce risk



www.etlsolutions.com
Data migration: A risk!
A real-life example of the risks involved

We were called in to rescue a project in which tools had
not been used:

• The vendor hand-wrote the migration
  to target system
• Rewritten three times due to:
    • Structural limitations
    • Performance (twice)
• Bugs in code delayed the migration
• Bugs in code caused incorrect data,
  making it difficult to test actual migration
   logic
Recommended best practice


 Business ownership: transparency,
  control, engagement
 Use of toolsets
 Use of a project management
  methodology
 A team with skills and experience in
  data migration
 Use standards wherever applicable
 Use of a data migration methodology
Recommended team leader objectives


 Identify and mitigate risks
 Ensure confidence in the project
  team
 Appropriate resourcing
 Keep the project on track:
    Within budget
    On time
 Reduce the overall cost and effort
  needed
Overview of our recommended data migration process


                      Business
                     engagement




      Scoping           Core           Legacy
                      migration    decommissioning




                    Assessments
Embed best practice within the process

•   Migration methodology: an in-depth process
    for each stage of the data migration, bringing
    in specialists at key times and working to a
    structured plan and documents
•   Project management methodology: We use
    PRINCE2 to ensure that the migration is well
    managed to a common standard
•   ISO standards: We use 15288,12207,and
    8000 to ensure the methodologies have a
    core standard structure
•   Migration software: The core migration steps
    should be carried out using a well established
    tool
•   Migration specialists: Specialists should be
    available for the duration of the project
Data migration process: Assessments

    Staff competency assessment                   Project assessment

•    Helps to identify gaps in the       •   A strategic review of the
     existing skill base                     proposed project, examining:
•    Shows where training may be              •   Plans
     required                                 •   Processes
•    Reduces reliance on external             •   Workflows
     experts                                  •   Data targets
•    Grows the confidence of the              •   Systems
     project team                        •   Identifies and mitigates risks
•    Provides individuals with greater       and issues before they occur
     clarity about their roles
•    Our proprietary Data Migration
     Competency Framework is
     designed specifically to support
     data migration teams
Data migration process: Scoping

           Project scoping                         Technical scoping

•   A detailed, tactical examination     •   A detailed examination of the
    of the proposed project,                 project’s technical structure:
    including:                                •   Available models
     •   Stakeholders and deliverables        •   Available software
         expected                             •   Data volume and quality
     •   Budgets
                                         •   Identifies potential technical
     •   Deadlines                           issues before they occur
     •   Communication plans
     •   Available experts: business
         domain, systems, migration
         experts
•   Helps with project planning to
    mitigate risk
•   Provides business leaders with
    a clear view of the project plan
Data migration methodology
           Iterative agile development is used throughout

   Project scoping
                                                                           Core migration
    Configuration


                        Landscape analysis   Data assurance   Migration design          Migration development

Requirements analysis     Data discovery       Data review
                                                              Testing design            Testing development
                          Data modelling     Data cleansing



                                                                            Execution


                                                                               Review




                                                                     Legacy decommissioning
Landscape analysis in more detail

• Landscape analysis encompasses the
  systematic process of identifying all
  source and target systems that may be
  involved in the data migration
• Gain an overview of the source and
  target systems
• Key tasks:
   •   Understand how each system works
   •   Understand how the data within each system
       is structured
   •   Model the systems
   •   Model links and interactions between systems
   •   Model data structures
Data assurance in more detail

• Data assurance puts measures
  in place to ensure that all        Data assurance questions:
  information used within the        •   What data migration and
  data migration is handled              profiling tools are available?
  accurately                         •   Are there key areas of
• Data quality is a key element,         weakness in data?
  along with data cleansing          •   Are rules for the data quality
  where required                         (attribute and relational) within
• Planning is required for the           the source already
                                         documented?
  retirement of data, for deletion
                                     •   Which governing rules have to
  or for storage due to industry
                                         be applied to the data?
  regulations
                                     •   Will all data be migrated?
• Key tasks:
    •   Data review
    •   Data cleansing
The key data assurance tasks
              Data review                               Data cleansing
•   Profiling is carried out to identify   •   Define the cleansing rules which
    areas of the data that may not             will be carried out manually and
    be of sufficient quality to meet           those which will be automated:
    business requirements                       •   The manual cleansing will be
•   Data quality definitions define                 typically be carried out prior to
    the quality that must be attained               migration
    for elements, attributes and                •   The automated cleansing will be
    relationships within the source                 carried out as a first step of the
                                                    migration or indeed may also be
    system; these definitions will be
                                                    able to be carried out prior to
    used during the profiling to                    migration
    verify if the data adheres to the
                                           •   Data verification is focused on the
    rules defined
                                               checking of data being available,
•   The system retirement plan                 accessible, in the correct format
    defines which data will be                 and complete
    moved from the old system to
                                           •   Data impact analysis is carried
    the new and what is no longer
                                               out to evaluate the effect on other
    required
                                               elements and systems
What happens when data assurance is omitted?
 • Multinational 3-way multi-company venture
 • US vendor migrating data
 • UK project management

 •   No migration management
 •   Lack of resource
 •   No verification or quality rules
 •   No profiling carried out
 •   Ad-hoc testing


 •   Security delays of 6 months
 •   Testing time increased by 3 months
 •   1 month delay for invalid characters
 •   Additional dry-run required due to issues encountered
Core migration in more detail

• Use a structured approach with methodologies to guide the
  process
• Establish clear structures and boundaries: a methodology will
  help with this
• Ensure tool-based execution: we use our own commercially
  available software, Transformation Manager
• Carry out tool-based testing
• Create an organisation-focused go live: scoping the project at
  an early stage can assist in disseminating the information to
  stakeholders around timings and resource required to achieve
  the goals
A core migration design
Our offerings for data management


       Transformation                    Data
       Manager data                    migration
         movement                      packaged
          software                      services




                          Support,
                        training and
                         mentoring
                          services
Why Transformation Manager?

For the user:    Everything under one roof
                 Greater control and
                  transparency
                 Identify and test against errors
                  iteratively
                 Greater understanding of the
                  transformation requirement
                 Automatically document
                 Re-use and change
                  management
                 Uses domain specific
                  terminology in the mapping
Why Transformation Manager?

For the business:    Reduces cost and effort
                     Reduces risk in the project
                     Delivers higher quality and
                      reduces error
                     Increases control and
                      transparency in the
                      development
                     Single product
                     Reduces time to market
Contact us for more information:
   Karl Glenn, Business Development Director
   kg@etlsolutions.com
   +44 (0) 1912 894040


   Read more on our website:
   www.etlsolutions.com




                                                                                Raising data
                                                                                management
                                                                                 standards
www.etlsolutions.com
 www.etlsolutions.com
                        Images from Free Digital Photos freedigitalphotos.net

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Migrating data: How to reduce risk

  • 1. Migrating data: How to reduce risk www.etlsolutions.com
  • 3. A real-life example of the risks involved We were called in to rescue a project in which tools had not been used: • The vendor hand-wrote the migration to target system • Rewritten three times due to: • Structural limitations • Performance (twice) • Bugs in code delayed the migration • Bugs in code caused incorrect data, making it difficult to test actual migration logic
  • 4. Recommended best practice  Business ownership: transparency, control, engagement  Use of toolsets  Use of a project management methodology  A team with skills and experience in data migration  Use standards wherever applicable  Use of a data migration methodology
  • 5. Recommended team leader objectives  Identify and mitigate risks  Ensure confidence in the project team  Appropriate resourcing  Keep the project on track:  Within budget  On time  Reduce the overall cost and effort needed
  • 6. Overview of our recommended data migration process Business engagement Scoping Core Legacy migration decommissioning Assessments
  • 7. Embed best practice within the process • Migration methodology: an in-depth process for each stage of the data migration, bringing in specialists at key times and working to a structured plan and documents • Project management methodology: We use PRINCE2 to ensure that the migration is well managed to a common standard • ISO standards: We use 15288,12207,and 8000 to ensure the methodologies have a core standard structure • Migration software: The core migration steps should be carried out using a well established tool • Migration specialists: Specialists should be available for the duration of the project
  • 8. Data migration process: Assessments Staff competency assessment Project assessment • Helps to identify gaps in the • A strategic review of the existing skill base proposed project, examining: • Shows where training may be • Plans required • Processes • Reduces reliance on external • Workflows experts • Data targets • Grows the confidence of the • Systems project team • Identifies and mitigates risks • Provides individuals with greater and issues before they occur clarity about their roles • Our proprietary Data Migration Competency Framework is designed specifically to support data migration teams
  • 9. Data migration process: Scoping Project scoping Technical scoping • A detailed, tactical examination • A detailed examination of the of the proposed project, project’s technical structure: including: • Available models • Stakeholders and deliverables • Available software expected • Data volume and quality • Budgets • Identifies potential technical • Deadlines issues before they occur • Communication plans • Available experts: business domain, systems, migration experts • Helps with project planning to mitigate risk • Provides business leaders with a clear view of the project plan
  • 10. Data migration methodology Iterative agile development is used throughout Project scoping Core migration Configuration Landscape analysis Data assurance Migration design Migration development Requirements analysis Data discovery Data review Testing design Testing development Data modelling Data cleansing Execution Review Legacy decommissioning
  • 11. Landscape analysis in more detail • Landscape analysis encompasses the systematic process of identifying all source and target systems that may be involved in the data migration • Gain an overview of the source and target systems • Key tasks: • Understand how each system works • Understand how the data within each system is structured • Model the systems • Model links and interactions between systems • Model data structures
  • 12. Data assurance in more detail • Data assurance puts measures in place to ensure that all Data assurance questions: information used within the • What data migration and data migration is handled profiling tools are available? accurately • Are there key areas of • Data quality is a key element, weakness in data? along with data cleansing • Are rules for the data quality where required (attribute and relational) within • Planning is required for the the source already documented? retirement of data, for deletion • Which governing rules have to or for storage due to industry be applied to the data? regulations • Will all data be migrated? • Key tasks: • Data review • Data cleansing
  • 13. The key data assurance tasks Data review Data cleansing • Profiling is carried out to identify • Define the cleansing rules which areas of the data that may not will be carried out manually and be of sufficient quality to meet those which will be automated: business requirements • The manual cleansing will be • Data quality definitions define typically be carried out prior to the quality that must be attained migration for elements, attributes and • The automated cleansing will be relationships within the source carried out as a first step of the migration or indeed may also be system; these definitions will be able to be carried out prior to used during the profiling to migration verify if the data adheres to the • Data verification is focused on the rules defined checking of data being available, • The system retirement plan accessible, in the correct format defines which data will be and complete moved from the old system to • Data impact analysis is carried the new and what is no longer out to evaluate the effect on other required elements and systems
  • 14. What happens when data assurance is omitted? • Multinational 3-way multi-company venture • US vendor migrating data • UK project management • No migration management • Lack of resource • No verification or quality rules • No profiling carried out • Ad-hoc testing • Security delays of 6 months • Testing time increased by 3 months • 1 month delay for invalid characters • Additional dry-run required due to issues encountered
  • 15. Core migration in more detail • Use a structured approach with methodologies to guide the process • Establish clear structures and boundaries: a methodology will help with this • Ensure tool-based execution: we use our own commercially available software, Transformation Manager • Carry out tool-based testing • Create an organisation-focused go live: scoping the project at an early stage can assist in disseminating the information to stakeholders around timings and resource required to achieve the goals
  • 17. Our offerings for data management Transformation Data Manager data migration movement packaged software services Support, training and mentoring services
  • 18. Why Transformation Manager? For the user:  Everything under one roof  Greater control and transparency  Identify and test against errors iteratively  Greater understanding of the transformation requirement  Automatically document  Re-use and change management  Uses domain specific terminology in the mapping
  • 19. Why Transformation Manager? For the business:  Reduces cost and effort  Reduces risk in the project  Delivers higher quality and reduces error  Increases control and transparency in the development  Single product  Reduces time to market
  • 20. Contact us for more information: Karl Glenn, Business Development Director kg@etlsolutions.com +44 (0) 1912 894040 Read more on our website: www.etlsolutions.com Raising data management standards www.etlsolutions.com www.etlsolutions.com Images from Free Digital Photos freedigitalphotos.net