a case study: tri-state's enterprise data...
TRANSCRIPT
Delivering Oracle Success
A CASE STUDY: TRI-STATE'S ENTERPRISE
DATA DICTIONARY
Jim Plummer, DBAKJan Hill, Tri-State G&T
RMOUG Training DaysFebruary 16, 2012
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Agenda
IntroductionsAbout Tri-State Project Background• Understanding the Enterprise Data Dictionary• Understanding Tri-State• Growth and Application Sprawl
The Enterprise Data Dictionary Project• Approach• Keys to Success
Managing the Enterprise Data Dictionary• EDDIE
Project Results
PresentersJim Plummer• DBAK Managing Principal and VP of Technology Services • Began working with Oracle Database Technology in 1985• Project Director and Architect on this Project
Jan Hill• Tri-State Data Architect• Joined Tri-State in 1995• Oracle EBS Development, including recent R12 Upgrade
Bryan Stroble• DBAK Enterprise Architect• Data Warehouse architecture, development, system
integration, large scale data processing and conversion• Lead Architect on this Project
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About DBAKOracle Solution Provider and License ResellerCore Technology and EBS ApplicationsColorado Owned and OperatedAverage 15 Years of Oracle Expertise “Top 250 Private Companies, 2011” – CoBIZ Magazine “Emerging Business of the Year, 2008” – South Metro Denver Chamber of Commerce100+ Clients170+ Implementations, Upgrades, Conversions, Support ProjectsOracle Gold PartnerOEM “Specialized”
About Tri-StateTri-State Generation and Transmission• Wholesale electric power supplier• Owned by 44 electric cooperatives• 200,000 sq. mile service territory
– Colorado, Nebraska, New Mexico, Wyoming
• 1.5 million consumers• Founded in 1952• Today: 1,2000 employees
Power Generation• Coal, natural gas, hydro-electric,
solar, wind
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Tri-State’s Growth
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From 26 rural electric cooperatives to 44From 41,000 end-use consumers to 1.5 millionAcquisitions• Generating plants, mines• Capital projects: Cimarron Solar Project
IT Infrastructure• 1990: 4 servers; today: over 400• Email to Client/Server to Web Applications• Oracle EBS, SAS, Ventyx Asset Suite, OBIEE• Hundreds of custom applications• Specialized Generation, Transmission, Trading, Operating and
Monitoring systems
Challenges from GrowthWith over 400 applications, and growing• Technology challenges
– Maintenance– Differing technologies– IT staffing levels stay constant as applications grow– Knowledge not documented– Data in conflict
New market pressuresApproval to create Enterprise Data Dictionary• Foundation for IT strategy• Enterprise Reporting• Integration• Improved member services
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The Enterprise Data DictionaryCollection of information that describes: • Information system data• Relationships between data• Consumption and generation of data within the
enterprise• Data used by the business to deliver products and
services to customersAlso known as meta-data• Data describing data• Helps us understand how data is used, and by what
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Corporate PerformanceRelies on data for:• Measuring against goals• Meeting regulatory standards• Expectations of customers, shareholders, etc.
IT must deliver the answers• Reports• Multiple sources• Sometimes inconsistent• What is the best source?
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Enterprise Data Dictionary provides• Roadmap• Simplifies the complexity• Consistency• Foundation for:
– Data warehouse– Enterprise reporting– Master Data
Management
The Roadmap
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“CUSTOMER”
CRM AP
AR
SelfService
Access
Excel
Custom
Cloud
Warehouse
Enterprise Data Dictionary ProjectProject Goals1. Reference of all applications2. Understandable to business users3. Capture application data fit to Enterprise structures
a. Business rulesb. Validation rules
4. Determine system of record for primary data elements5. Determine what data elements are used for reporting6. Determine data conflicts across applications7. Determine data elements no longer used8. Enable application consolidation and elimination
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Project ApproachPhase 1 began in April 2011• Document the data and application inventory• Project goals 1 and 2
Future analysis phases• Project goals 3 to 7
Iterative approach• Bottom up
– Inspect– Classify– Consolidate– Refine– Standardize
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Entities and AssociationsEntity• Generalized, summary level, meaningful name• High Level Entity• Mid Level Entity
Association• Descriptive relationship between two Entities
– STORED AS– HAS– ASSOCIATED WITH
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Example: BANKBANK – STORED AS – BANKBANK – HAS – ADDRESSBANK – HAS – NAMEBANK – HAS – LOCATIONBANK – HAS – ROUTE CODEBANK – HAS – ACCOUNT NUMBERBANK – ASSOCIATED WITH – CHECK EMPLOYEE – ASSOCIATED WITH – BANKPAYABLE – ASSOCIATED WITH – CHECKPAYABLE – ASSOCIATED WITH - SUPPLIER
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Bottom Up: GL Budget
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BUDGET “STORED AS”
BUDGET
BUDGET “HAS”
VERSION
BUDGET “ASSOCIATED WITH”
GL ACCOUNT
Iterative Approach1. Application Inventory2. Entity and Association Inventory
a. Application, Module, Functionb. Physical Location (Schema and Table Name)c. Note – Analysis behind the decisions maded. Source documents – Basis for decisions, background
info3. Review, consolidate, standardize across applications
a. Draw an entity map – visualize the inventory4. Review with SMEs5. Define Enterprise Entities
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Entity Map
Visualize decisionsAre all entities high level?• Attributes?• Associations?
Time Sheet• Good!
Person• Good!
Assessment• No associations
Duty Area• No Mid-Level Entities• Only 2 associations
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Enterprise Entity
Higher level summary of Entities• 50 or less
Enterprise: EXPENSEPROJECT COSTPAYROLLPAYMENTPAYABLELIABILITYTIME SHEETINTEREST RATEEXPENSE REPORTEXPENSECREDIT AMOUNTRISKINVOICE
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Application High Level Entities
Managing the Data DictionaryOver 2,000 entities, 6,500 associations, 400 applications• Cannot manage within a set of Excel files
DBAK built an Oracle Application Express database application• EDDIE
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EDDIEEnterprise Data Dictionary Information Exchange• Application and Entity: Search and browse• Create, update, delete capabilities• Term search provides for use of alternate entity names• Application category interactive search and browse• Entity Usage interactive search and browse• QA reports to manage data dictionary quality• Dashboard view of activity and inventory• Administrative management functions• Help through video tutorials
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EDDIE Demonstration
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Keys for Rich Meta-DataBottom up approachCapture physical locationBuild taxonomy and synonymsCapture source documentsMake a decision!• Just decide; you can change it later
Capture sensitive data indicator
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Results10 months, 2.5 FTE• Enterprise architects, Data Architects, Data Modeler, APEX
developerImmediate benefits in analyzing application impacts due to business or system changesSkeptics have become believersNot a 100% solution• It is a roadmap of the data
– Like with a car, Google Maps does not tell you how to drive
Forms the foundation of future application, reporting, data management, and integration efforts
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Questions
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Contact Jim Plummer720.475-8600
Presentation available at:www.dbaknow.com/downloads
www.dbaknow.com