State of Wisconsin Department of Revenue Data Warehouse Presentation August 16, 2000

2 Agenda n Purpose of the WIRED Project n Development Timeline n Technical Process n Subject Areas n Development Challenges n Lessons Learned n Audit Bureau Changes n Audit Selection Efficiencies n Demonstration n Summary of Advantages n Questions & Answers $ $ $ $ $ $ $ $

3 Purpose of the WIRED Project n Generate sufficient audit candidates to enable work units to produce an additional $4.78 million in revenue n Increase flexibility and efficiency of access to Sales & Use and Corporate Tax Data n Develop plan for data warehouse growth and support n Increased familiarity and comfort with data warehouse concepts and tools n Improve efficiency of business tax audit project selection W arehouse for I ntegrated R evenue E nterprise D ata

4 Development Timeline Business Requirements Definition for Pilot Data Architecture- Pilot Data Access and Transformation Strategy Train Developers Implement ETL Requirements Develop Business Objects Universes System Testing Data Validation Pilot Production Loading & Revalidation Train Users Dec Jan Feb Mar Apr May Jun User Acceptance Testing

5 Technical Process - High Level n Data loaded on a monthly basis n Corp Extract and Match file are used to drive other monthly reporting needs New Detail Flat File New Relational DB/2 Operational Data Store New Relational DB/2 Data Warehouse, Metadata Repository Existing NT Web Server Users - Business Objects & Web MetaData Browser Corporate Tax System DB/2 Sales & Use Tax System IMS Existing Matched Key File New Registered Non-Filer Corp File Existing DB/2 Extract Table Transformation, Cleansing & Loading Transformation and Aggregation

6 Technical Process – Focus on ETL S/U Taxpayer S/U Return Detail Corp. Taxpayer Corp. Return Detail Extract S/U & Load ODS Extract Corp & Load ODS Load Corp Non- Filers to ODS Mainframe ODS In the ODS: - Data Validation Load DW Taxpayer Fact Load DW S/U Return Fact Load DW Corp Return Fact DW In the DW: - Aggregate S/U & Corp to tax year - Create S/U & Corp non-filer records - Create “Invalid” dimension values Taxpayer Fact S/U Return Fact Corp. Return Fact Aggregate S/U and Corp Fact

7 Subject Areas Penalties Tax Registration Audit History Receipts Subtractions Credits Assets Apportionment Losses

8 Development Challenges n Scope of project n Using Match file in the S/U & Corp match-merge process n Matching and aggregating of tax return data n S/U Timestamp n Method for handling Corp and S/U Non- Filers n Method for handling S/U Audit History data n Corp Extract errors n Speed of loading the ODS and DW

9 Lessons Learned n Clear scope is critical to success n Quality is more important than quantity n Build transition into the project plan

10 Re-engineering the Audit Bureau Each functional unit (corporate, sales, field and Nexus) worked independently Each functional unit (corporate, sales, field and Nexus) worked independently Little opportunity for Audit staff to share information and work collaboratively on projects Little opportunity for Audit staff to share information and work collaboratively on projects No system support for Audit projects No system support for Audit projects Little communication and planning for upcoming project with DOR units outside of Audit (e.g. central files, mailing, etc.) Little communication and planning for upcoming project with DOR units outside of Audit (e.g. central files, mailing, etc.) Functional unit members combined into new, multi- functional team Multi-functional team collaborates on audit projects based on shared information from the data warehouse Staff has opportunity to learn new IT skills Staff has opportunity to take part in progressive and innovative project Before After

11 Efficiencies in Audit Selection Decrease in average and amount of time per field audit selected and assigned Decrease in average and amount of time per field audit selected and assigned Data Warehouse provides easy way to investigate taxpayer groups and segments Data Warehouse provides easy way to investigate taxpayer groups and segments Ability to investigate multiple data points for a taxpayer Ability to investigate multiple data points for a taxpayer

12 Demonstration

13 Summary of Advantages Common Definitions for Business Terms and Data Common Definitions for Business Terms and Data Highly Flexible Environment Highly Flexible Environment –Ease of “getting the data out” Faster Response to Requests for Reports and Data Faster Response to Requests for Reports and Data –Reduction of staff effort to answer a question Standardized Way of Approaching a Question Standardized Way of Approaching a Question –Construction of selection logic –Extraction and transformation of data –Data are pre-validated –Report sharing through the Business Objects repository

14 Questions & Answers