Dave Gordon The Data Conversion Cycle Technical Project

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

Dave Gordon HCM Transformation Consultant The Practicing IT Project Manager, LLC davegordon@practicingitpm. com www. greatpro. org Hosted by Wendy Nolan The Great IT Professional Wendy_Nolan@compaid. com

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/ 3 Title of Presentation

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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 7 The Data Conversion Cycle

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 • • 8 The Data Conversion Cycle

An Iterative Approach 9 The Data Conversion Cycle

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 10 The Data Conversion Cycle

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 11 The Data Conversion Cycle

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 12 The Data Conversion Cycle

Define Conversion Scope 13 The Data Conversion Cycle

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 14 The Data Conversion Cycle

Map Records to Target 15 The Data Conversion Cycle

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 16 The Data Conversion Cycle

Legacy System Extraction Processes 17 The Data Conversion Cycle

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 • • • 18 The Data Conversion Cycle

Extract & Load to Target System 19 The Data Conversion Cycle

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! • • 20 The Data Conversion Cycle

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 21 The Data Conversion Cycle

Validate Conversion Load 22 The Data Conversion Cycle

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 23 The Data Conversion Cycle

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 24 The Data Conversion Cycle

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! • • 25 The Data Conversion Cycle

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Dave Gordon HCM Transformation Consultant The Practicing IT Project Manager, LLC davegordon@practicingitpm. com www. greatpro. org Hosted by Wendy Nolan The Great IT Professional Wendy_Nolan@compaid. com

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