The Data Conversion Cycle

1. Dave Gordon The Data Conversion Cycle Technical Project Management October 10, 2018 11:00 am EST www.greatpro.org

2. Dave Gordon Dave GordonHCM Transformation ConsultantThe Practicing IT Project Manager, LLCdavegordon@practicingitpm.com Hosted by Wendy Nolan The Great IT Professional Wendy_Nolan@compaid.com www.greatpro.org

3. About the Presenter Dave Gordon consults on HCM transformation, providing project and program management services for global firms. He has authored or contributed to several books and hundreds of articles on project management. He also curates a weekly list of new web content of interest to project managers at: http://blog.practicingitpm.com/ Title of Presentation

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7. The Data Conversion Cycle • A generalized approach to migrating data records to a new transaction processing system • Independent of business domain, project management methodology, software products and technology • Designed for use by cross-functional teams • Intended to facilitate a shared understanding through use of a common vocabulary The Data Conversion Cycle

8. Basic Principles • Planned iteration of a basic cycle • Simplified initial requirements • Add complexity in subsequent cycles • Continuous refinement based on inspection of results • Just enough documentation to support the work at hand The Data Conversion Cycle

9. An Iterative Approach The Data Conversion Cycle

10. Typical Project Team Roles • Data Custodians – primary expertise is business domain • Database Administrators – primary expertise is managing database technology • Project Managers • Conversion Leads • Testing and Validation Leads • Project Sponsors The Data Conversion Cycle

11. A Shared Vocabulary • Field: contains a single data element • Record Type: a list of fields in a record • Record: a single instance of data of a particular record type • File: a collection of records, usually of a single type • Table: in a relational database, a container for records of a particular type The Data Conversion Cycle

12. A Shared Vocabulary • Parent-Child Relationship: a child record includes additional attributes of a parent record; usually one-to-many • Key Field: one or more fields that uniquely identify a record • Local Key: identifies itself • Remote Key: refers to another record • Referential Integrity: quality of remote links The Data Conversion Cycle

13. Define Conversion Scope The Data Conversion Cycle

14. Discover what needs to be done • Identify all sources, on-line and off • Based on record retention policies: keep in production, archive, or purge? Exceptions? • Controls required: access, destruction • Intent for legacy system? Decommissioning? • Number of conversion cycles needed: development, test, transition to production • Define detailed scope for each iteration The Data Conversion Cycle

15. Map Records to Target The Data Conversion Cycle

16. Data Assumes The Shape of Its Container • Data mapping: an analytical process that results in rules for transforming data elements captured in one data model to have equivalent meaning under a different data model • Collaboration between respective product experts, DBA and Data Custodians • Referential integrity and keys • Conventions for creating new data elements The Data Conversion Cycle

17. Legacy System Extraction Processes The Data Conversion Cycle

18. Reproducible Data Extraction • Use a secured static copy of legacy Production • Identify dependencies and sequence • Determine exception handling rules • Establish communication protocols for issues • Identify decision makers for issues and decisions • Prepare audit reports to confirm extraction of records in scope The Data Conversion Cycle

19. Extract & Load to Target System The Data Conversion Cycle

20. Extraction: Key Actions • If necessary, refresh static copy of Production • Run audit reports to get accurate record counts • Execute extraction processes • Compare results of the load processes to audit record counts • Transfer extracted records using secure means, to a secure file server! The Data Conversion Cycle

21. Load: Key Actions • Ensure load process sequence is followed to preserve referential integrity • Preserve all exceptions for analysis in Validation • Run audit reports on loaded records and compare to extraction reports • Identify needed corrections to Target system configuration that impacted loading The Data Conversion Cycle

22. Validate Conversion Load The Data Conversion Cycle

23. Preparing for Validation • Goal: minimize the time required to validate! • Identify specific records to validate • Identify application user roles with access required to access and validate loaded records • Review delivered audit reports and identify gaps; create new reports before loading • Identify fields which are better compared via automated means, e.g. Excel The Data Conversion Cycle

24. Validate the Target System • Application-level comparison: log into both systems at the same time to identify mapping errors • Report-level comparison: inspect for truncated values, duplicates, omissions, and other errors in the extraction processes • Inspect load process logs for errors to be corrected in Production records The Data Conversion Cycle

25. Create a Plan! • List all constraints and assumptions • Based on scope, identify tasks for each iteration • Identify dependencies between workstreams • Estimate duration for each task—optimistic, worst case, and most likely—for each iteration • Identify who will participate in each step of the process • Identify and manage risks! The Data Conversion Cycle

26. Buy My Book! • Available on Amazon • Paperback: $6.99 • Kindle: $4.49 • Only 88 pages! The Data Conversion Cycle

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31. Dave Gordon Dave GordonHCM Transformation ConsultantThe Practicing IT Project Manager, LLCdavegordon@practicingitpm.com Hosted by Wendy Nolan The Great IT Professional Wendy_Nolan@compaid.com www.greatpro.org

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