Data Conversion Services

The Vendor is required to provide data profiling, data cleansing, and data migration technical services to agency in support of the implementation of a new pension administration system (PAS).
- Services must include:
• Managing and leading a large data project
• Data profiling, analysis and summarization
• Automated data cleansing tools and techniques
• Architecting and developing an intermediate staging database for migrating data from one system to another
• Data extraction, transformation and loading from multiple sources including Excel spreadsheets
• Quality assurance, quality control and data verification
• Project management and planning for data migrations
- Data profiling, cleansing and validation of existing system
• Lead a data profiling, cleansing, validation and migration project to move data from one system to another through the use of an intermediary staging database.
• Provide multiple environments for data activities as required to successfully complete the project.
• Conduct thorough data profiling to identify data quality issues.
• Cleanse and validate data.
• Ensure data consistency, accuracy and completeness.
• Design and build multiple environments for data conversion as required.
• Produce detailed documentation to allow agency to retain an audit history of all activities performed.
- Data project management:
1. Conduct a project kickoff meeting.
2. Develop a detailed project plan that covers all project activities and includes all milestones and resources necessary for successfully completing the project.
3. Collaborate with agency to:
• Define and document the data profiling strategy and approach
• Identify the resources and responsibilities required to assist with the project
• Agree on and document a glossary of terms that will be used to communicate throughout the project with the other project teams
• Establish procedures for issue resolution
4. Produce project status reports at agreed upon intervals.
5. Produce meeting minutes including action items, decisions made, and summary of major topics for all data related meetings.
6. Provide tools, processes, and automation to support the data analysis, data cleansing, validation, and data migration services. 
7. Identify any tools agency needs to provide.
- Data profiling:
• Overall coordination of the data cleansing, data migration, and data validation activities.
• Configure all tooling as needed for data profiling activities.
• Analyze existing data in current systems (legacy system, star and the new employer reporting proprietary system, Gemini, as well as ancillary data structures that support agency business functions) to identify anomalies, inconsistencies, and inaccuracies.
• Create and tune scripts to perform data profiling.
• Generate data profiling reports to document findings.
• Define data quality metrics and thresholds.
• Produce a data mapping schema for all data sources being used to load the staging database, and revise that schema as required throughout the design and testing phases.
- Data cleansing:
1. Collaborate with agency to design all necessary SQL staging database(s) for data cleansing; agency intends for the final staging database to be utilized by the pension administration software vendor for data migration.
2. Configure all tooling as needed for data cleansing activities.
3. Develop initial data cleansing strategies and an on-going strategy to validate and reconcile data as needed during data migration project activities.
4. Provide a prioritized list of data elements (e.g. age, grouping, status, class) to be cleansed.
5. Document all formulas and processes used to cleanse data.
6. Produce a data mapping schema for all the data sources being used to load the staging database and revise that schema as required throughout the design and testing phases.
7. Create and tune scripts to perform data cleansing.
8. Identify and correct data issues including but not limited to:
• Duplicates
• Missing primary-foreign key relationships
• Missing values
• Incorrect formats
• Incorrect data based on a numeric range
• Incorrect data based on relationship rules
• Incorrect dates based on expected ranges
• Non-unique keys
• Incomplete data elements based on business rules, policies, and statutes
• Referential integrity
• Orphaned records (records that should be associated to others but are not)
• Childless parents (records that should have related records but do not)
• Invalid codes
• Varied data values (same code used in different places with different meanings)
• Conflicting amount totals vs. summarized detail
• Amount deltas based on business rules, policies, and statutes
9. Standardize data formats and values.
10. Validate cleansed data against defined quality metrics.
11. Provide physical data models (source and target), data definitions, and source to target mapping documentation, including transformations.
12. Produce a data dictionary for the staging database.
13. Provide data analysis reports (e.g., description of problem, data source, and number of occurrences, impact on production data, type of fix that was applied, number of records fixed, and number of records unable to be fixed).
14. Retain history (audit trail) of all data elements that are changed through cleansing (before and after) and conversion.
15. Provide an on-going data cleansing maintenance plan.
- Contract Period/Term: 1 year
- Questions/Inquires Deadline: June 27, 2025