State of Wisconsin State of Wisconsin Department of RevenueDepartment of Revenue

Data Warehouse PresentationData Warehouse Presentation

August 16, 2000August 16, 2000

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AgendaAgenda Purpose of the WIRED ProjectPurpose of the WIRED Project Development TimelineDevelopment Timeline Technical ProcessTechnical Process Subject AreasSubject Areas Development ChallengesDevelopment Challenges Lessons LearnedLessons Learned Audit Bureau ChangesAudit Bureau Changes Audit Selection EfficienciesAudit Selection Efficiencies DemonstrationDemonstration Summary of AdvantagesSummary of Advantages Questions & AnswersQuestions & Answers

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Purpose of the WIRED Purpose of the WIRED ProjectProject

Generate sufficient audit Generate sufficient audit candidates to enable work units to candidates to enable work units to produce an additional produce an additional $4.78 $4.78 millionmillion in revenue in revenue

Increase flexibility and efficiency of Increase flexibility and efficiency of access to Sales & Use and access to Sales & Use and Corporate Tax DataCorporate Tax Data

Develop plan for data warehouse Develop plan for data warehouse growth and supportgrowth and support

Increased familiarity and comfort Increased familiarity and comfort with data warehouse concepts and with data warehouse concepts and toolstools

Improve efficiency of business tax Improve efficiency of business tax audit project selectionaudit project selectionWarehouse for

Integrated Revenue

Enterprise Data

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Development TimelineDevelopment 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

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Technical Process - High Technical Process - High LevelLevel

Data loaded on a monthly basisData loaded on a monthly basis Corp Extract and Match file are used to drive other monthly Corp Extract and Match file are used to drive other monthly

reporting needsreporting needs

NewDetail

Flat File

New Relational DB/2 Operational

Data Store

New Relational DB/2Data Warehouse,

Metadata RepositoryExisting

NT Web Server

Users - Business Objects &Web MetaData Browser

Corporate Corporate Tax SystemTax System

DB/2DB/2

Sales & Use Tax SystemSales & Use Tax SystemIMSIMS

ExistingMatched Key File

NewRegistered Non-Filer Corp File

Existing DB/2

Extract Table

Tra

nsfo

rma

tion

, C

lean

sing

& L

oad

ing

Tra

nsfo

rma

tion

and

Agg

reg

atio

n

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Technical Process – Focus on ETLTechnical Process – Focus on ETL

S/UTaxpayer

S/UReturnDetail

Corp.Taxpayer

Corp.ReturnDetail

Extract S/U & Load ODS

Extract Corp & Load ODS

Load Corp Non-Filers to ODS

Mainframe

ODS

In the ODS:

- Data Validation

Load DWTaxpayer Fact

Load DWS/U Return Fact

Load DWCorp Return Fact

DW

In the DW:- Aggregate S/U & Corp to tax year- Create S/U & Corp non-filer records- Create “Invalid” dimension values

TaxpayerFact

S/UReturn

Fact

Corp.Return

Fact

AggregateS/U and Corp

Fact

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Subject AreasSubject Areas

PenaltiesTax Registration

Audit History

ReceiptsSubtractions

Credits

Assets

Apportionment

Losses

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Development ChallengesDevelopment Challenges Scope of projectScope of project Using Match file in the S/U & Corp Using Match file in the S/U & Corp

match-merge processmatch-merge process Matching and aggregating of tax return Matching and aggregating of tax return

datadata S/U TimestampS/U Timestamp Method for handling Corp and S/U Non-Method for handling Corp and S/U Non-

FilersFilers Method for handling S/U Audit History Method for handling S/U Audit History

datadata Corp Extract errorsCorp Extract errors Speed of loading the ODS and DWSpeed of loading the ODS and DW

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Lessons LearnedLessons Learned

Clear scope is Clear scope is critical to successcritical to success

Quality is more Quality is more important than important than quantityquantity

Build transition Build transition into the project into the project planplan

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Re-engineering the Audit Re-engineering the Audit BureauBureau

Each functional unit Each functional unit (corporate, sales, field and (corporate, sales, field and Nexus) worked Nexus) worked independentlyindependently

Little opportunity for Audit Little opportunity for Audit staff to share information staff to share information and work collaboratively on and work collaboratively on projectsprojects

No system support for No system support for Audit projectsAudit projects

Little communication and Little communication and planning for upcoming planning for upcoming project with DOR units project with DOR units outside of Audit (e.g. outside of Audit (e.g. central files, mailing, etc.)central files, mailing, etc.)

Functional unit members Functional unit members combined into new, combined into new, multi-functional teammulti-functional team

Multi-functional team Multi-functional team collaborates on audit collaborates on audit projects based on shared projects based on shared information from the information from the data warehousedata warehouse

Staff has opportunity to Staff has opportunity to learn new IT skillslearn new IT skills

Staff has opportunity to Staff has opportunity to take part in progressive take part in progressive and innovative projectand innovative project

BeforeBefore AfterAfter

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Efficiencies in Audit Efficiencies in Audit SelectionSelection

Decrease in average and Decrease in average and amount of time per field amount of time per field audit selected and audit selected and assignedassigned

Data Warehouse provides Data Warehouse provides easy way to investigate easy way to investigate taxpayer groups and taxpayer groups and segmentssegments

Ability to investigate Ability to investigate multiple data points for a multiple data points for a taxpayertaxpayer

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DemonstrationDemonstration

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Summary of AdvantagesSummary of Advantages Common Definitions for Business Terms and DataCommon Definitions for Business Terms and Data Highly Flexible EnvironmentHighly Flexible Environment

– Ease of “getting the data out”Ease of “getting the data out” Faster Response to Requests for Reports and Faster Response to Requests for Reports and

DataData– Reduction of staff effort to answer a questionReduction of staff effort to answer a question

Standardized Way of Approaching a QuestionStandardized Way of Approaching a Question– Construction of selection logicConstruction of selection logic– Extraction and transformation of dataExtraction and transformation of data– Data are pre-validatedData are pre-validated– Report sharing through the Business Objects repositoryReport sharing through the Business Objects repository

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Questions & AnswersQuestions & Answers