3.13 : Prepare Data for Mock Conversions (Data Cleansing & Data Mapping)
Objective
Jointly develop Data Conversion Plan informed by data cleansing; execute plan to address potential conversion issues.
View Lessons LearnedRecommended Best Practices
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Shared
Establish joint data governance for processes, roles, responsibilities, standards for cleansing & mapping
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Provider
Review customer current data architecture
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Shared
Provider and customer agency align on standard data management practices
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Shared
Finalize end-to-end plan for data cleansing, mapping, ETL, mock conversion, conversion, & validation
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Shared
Assess data quality based on data cleansing activities from prior phase against defined criteria
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Shared
Initiate legacy-to-target data mapping
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Shared
Identify data errors/anomalies and prioritize resolution activities
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Shared
Develop / execute Data Cleansing Scripts; Perform correction / updating, manually if needed
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Customer
Validate results of data cleansing / readiness for conversion based on data quality criteria and metrics
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Shared
Report updates in leadership / governance meetings thru Status Reports/Dashboards
3.13 Lessons Learned
- Start data cleansing early and prior to implementation; continue throughout to ensure readiness
- Agree on data governance, including metadata and data quality management
- Include post–Go-Live cleansing and quality tasks in data conversion strategy, schedule, and resourcing
- Review provider post–Go-Live support services before finalizing cleansing metrics
- Develop extraction procedures, tools, and protocols. Define system structure, major components, and type of conversion effort.
- Identify and address affected interfaces and security issues related to conversion efforts.
- Define hardware / software conversion steps, identify data and pre-conversion requirements, establish data quality assurance controls for conversion.
Stakeholders
Recommended stakeholders, inputs, & outputs may vary by implementation; however, agencies that contributed to this Playbook reported these factors as increasing the likelihood of success.Customer
- Program Manager
- Business Owner
- Functional Lead
- Technical Lead/Solution Architect
- Data Conversion Lead
- Data SME
Provider
- Program Manager
- Business Owner
- Functional Lead
- Technical Lead/Solution Architect
- Data Conversion Lead
- Data SME
Inputs
- Data Elements
- Data Cleansing Plan
- Data Quality Assessment Results
- Existing System Data Dictionaries
- Existing Data Governance Model
- Data Cleansing Results
- Existing Data Quality Assessment
Outputs
- Data Cleansing Scripts
- Documented Data Structure and Mapping
- Data Conversion Plan
- Status Reports/Dashboards
