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