Using OBIEE and Data Vault to Virtualize Your BI Environment: An Agile Approach


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First we interview the users, then we design a reporting model based on those interviews. We follow that up with mounds of ETL development to load the new model, basically keeping the user community in the dark during all that development. Does this sound familiar?

This presentation will demonstrate an alternative approach using the Data Vault Data Modeling technique to build a flexible, easily-extensible “Foundation” layer in our data warehouse with an Agile, iterative methodology. Relying on the Business Model and Mapping (BMM) functionality of OBIEE, we can rapidly virtualize a dimensional reporting model using the pattern-based Data Vault Foundation layer to decrease the time, and money, it takes to get BI content in front of end users. Attendees will see a sample Data Vault model designed iteratively and deployed to the semantic model of OBIEE.

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  • Using OBIEE and Data Vault to Virtualize Your BI Environment: An Agile Approach

    1. 1. Using OBIEE and Data Vault to Virtualize Your BI Environment: An Agile Approach Kent Graziano, Data Warrior LLC Stewart Bryson, Rittman Mead
    2. 2. Kent Graziano  Twitter: @KentGraziano  Certified Data Vault Master  Oracle ACE Director, Oracle BI&DW  Data Architecture and Data Warehouse Specialist ● 30+ years in IT ● 20+ years of Oracle-related work ● 15+ years of data warehousing experience  Co-Author of 2 Books ● The Business of Data Vault Modeling ● The Data Model Resource Book (1st Edition)  Editor of “The” Data Vault Book ● Super Charge Your Data Warehouse  Co-Chair BI/DW SIG for ODTUG  Past-President of Oracle Development Tools User Group and Rocky Mountain Oracle User Group
    3. 3. Stewart Bryson • Twitter : @StewartBryson • Oracle ACE in BI/DW • Oracle BI/DW Architect and Delivery Specialist • Community Speaker and Enthusiast • Writer for Rittman Mead Blog: • US Conference Chair of the Rittman Mead BI Forum • Developer of Transcend Framework • Email : • Real Time BI with Kevin & Stewart ‣ iTunes: ‣ YouTube:
    4. 4. About Rittman Mead • Oracle BI and DW Partner • World leader in solutions delivery and innovation in Oracle BI • Approximately 70 consultants worldwide • Offices in US (Atlanta), Europe, Australia and India • Skills in broad range of supporting Oracle BI Tools ‣ OBIEE ‣ OBIA ‣ ODIEE ‣ Essbase, Oracle OLAP ‣ GoldenGate ‣ Exadata ‣ Endeca
    5. 5. Questions We Hope to Answer • Data Vault ‣ What is Data Vault? ‣ Why would I choose Data Vault over competing technologies? • Oracle Information Management Reference Architecture ‣ What are the core components of the Reference Architecture? ‣ Is there possibly an acronym for that? • Oracle Business Intelligence ‣ What is OBIEE? ‣ Why does OBIEE work so well with Data Vault? • What is Agile BI and how does this help?
    6. 6. Oracle Information Management Reference Architecture  Staging Layer ● Change tables for Oracle GoldenGate ● Reject tables for Data Quality ● External tables for file feeds  Foundation Layer ● Transactional granularity maintained ● Process neutral: no user or business requirements ● Just recording what happened  Access and Performance Layer ● Dimensional model ● “Star Schemas” ● Process specific: targeting user and business requirements
    7. 7. What is Data Vault Trying to Solve?  What are our other Enterprise Data Warehouse options? ● Third-Normal Form (3NF): Complex primary keys (PK’s) with cascading snapshot dates ● Star Schema (Dimensional): Difficult to reengineer fact tables for granularity changes  Difficult to get it right the first time  Not adaptable to rapid business change  NOT AGILE!
    8. 8. Data Vault: Definition  The Data Vault is a detail oriented, historical tracking and uniquely linked set of normalized tables that support one or more functional areas of business.  It is a hybrid approach encompassing the best of breed between 3rd normal form (3NF) and star schema. The design is flexible, scalable, consistent, and adaptable to the needs of the enterprise. It is a data model that is architected specifically to meet the needs of today’s enterprise data warehouses. Dan Linstedt: Defining the Data Vault Article
    9. 9. Data Vault Timeline
    10. 10. What is the Foundation Layer? • Basis for long term enterprise scale data warehouse • Must be atomic level data ‣ A historical source of facts ‣ No user requirements applied • Not based on any one data source or system • Single point of integration • Flexible • Extensible • Provides data to the access/reporting layer ‣ Based on targeted business requirements ‣ Can be virtual
    11. 11. Standard Approach to Agile Business Intelligence • Design iterations around smaller chunks ‣ Iteration 1: Interviews and user requirements ‣ Iteration 2: Logical modeling ‣ Iteration 3: ETL Development ‣ Iteration 4: Front-end development • Requires 4 iterations before we get any usable content
    12. 12. Manifesto for Agile Software Development  “We are uncovering better ways of developing software by doing it and helping others do it.  Through this work we have come to value:  Individuals and interactions over processes and tools  Working software over comprehensive documentation  Customer collaboration over contract negotiation  Responding to change over following a plan  That is, while there is value in the items on the right, we value the items on the left more.” 
    13. 13. Applying the Agile Manifesto to BI Development  User Stories instead of requirements documents ● User asks for content or functionality through a narrative ● Typically includes current version of the report  Time-boxed iterations ● Iteration has a standard length ● Choose one or more user stories to fit in that iteration  Rework is part of the game ● There are no “missed requirements”... only those that haven’t been delivered yet.
    14. 14. What is Our Approach?  Model iteratively ● Use Data Vault data modeling technique ● Create basic components, then add over time  Virtualize the Access Layer ● Don’t waste time building facts and dimensions up front ● ETL and testing takes too long ● “Project” objects using pattern-based DV model with OBIEE BMM  Users see real reports with real data
    15. 15. Data Vault: Three Simple Structures
    16. 16. 1. Hub = Business Keys Hubs = Unique Lists of Business Keys Business Keys are used to TRACK and IDENTIFY key information
    17. 17. 2: Links = Associations Links = Transactions and Associations They are used to hook together multiple sets of information
    18. 18. 3. Satellites = Descriptors Satellites provide context for the Hubs and the Links
    19. 19. Flexibility (Agility) and Productivity • Adding new components to the EDW has NEAR ZERO impact to: ‣ Existing Loading Processes ‣ Existing Data Model ‣ Existing Reporting & BI Functions ‣ Existing Source Systems ‣ Existing Star Schemas and Data Marts • Standardized modeling rules ‣ Highly repeatable and learnable modeling technique ‣ Allows automation of models, loads, and extracts ‣ Can use a BI-meta layer to virtualize the reporting structures ‣ OBIEE Business Model and Mapping tool
    20. 20. What is OBIEE? •Dashboards, Ad-hoc Reporting, Alerts, Microsoft Office Integration • High quality graphical, role/user based views • Multiple views of same data •Point and click ease of use •Common Enterprise Information Model • Unified semantic/logical view of data from multiple sources • Heterogeneous database access • True enterprise deployment •Alerts, scheduling and distribution
    21. 21. Where Does OBIEE Fit? •OBIEE is the Information Access Layer •BI Abstraction layer allows us “bypass” the creation of the Access & Performance Layer •We “virtualize” the dependent data marts
    22. 22. Flow of Data Through the Three-Layer Semantic Model Simplification of the Data Model Integration of Disparate Data Sources Addition of Business Logic and Calculations Addition of Aggregate Sources
    23. 23. OBIEE Physical Model
    24. 24. OBIEE Tips and Tricks (Discovered by Stewart Bryson) • Create folders in the Physical Layer ‣ Separate Hubs, Links and Satellites ‣ Each has distinct uses • Hubs ‣ Business Keys ‣ Used in defining Primary Keys and Level Keys • Links ‣ Used in Extending the Logical Table Source (LTS) ‣ Never references in display columns or measures • Satellites ‣ Use these for Attributes and Measures ‣ Anything displayed to the user
    25. 25. Building a Simple Dimension: Mapping the Primary Key
    26. 26. Building a Simple Dimension: Renaming for Clarification
    27. 27. Building a Simple Dimension: Defining the Primary Key
    28. 28. Building a Simple Dimension: Extending the Logical Table Source (LTS)
    29. 29. Building a Simple Dimension: Adding Descriptive Attributes
    30. 30. Building a Simple Fact: Mapping Measures
    31. 31. Building a Simple Fact: Renaming for Clarification
    32. 32. Building a Simple Fact: Mapping the Primary Key
    33. 33. Building a Simple Fact: Extending the Logical Table Source (LTS)
    34. 34. Simple Dimension and Fact: An Analysis
    35. 35. Building a Factless Fact: Adding the LTS
    36. 36. Building a Factless Fact: Adding the “Fake” Count Measure
    37. 37. Links: Added to Logical Facts or Logical Dimensions? Logical Fact Logical Dimension
    38. 38. Links: Added to Logical Facts or Logical Dimensions?
    39. 39. “Link”-ing Levels Within a Hierarchy in a Logical Dimension
    40. 40. “Link”-ing Levels Within a Hierarchy in a Logical Dimension
    41. 41. Organizations Using Data Vault • WebMD Health Services • Anthem Blue-Cross Blue Shield • Denver Public Schools • Independent Purchasing Cooperative (IPC, Miami) • Owner of Subway • Kaplan • US Defense Department • Colorado Springs Utilities • State Court of Wyoming • Federal Express • US Dept. Of Agriculture
    42. 42. Summary • Data Vault provides a data modeling technique that allows: ‣ Model Agility ‣ Enabling rapid changes and additions ‣ Productivity ‣ Enabling low complexity systems with high value output at a rapid pace ‣ Easy projections of dimensional models • OBIEE provides ‣ Framework for Agile BI ‣ Rapid development of virtualized layer on a data vault model
    43. 43. Super Charge Your Data Warehouse Available on Soft Cover or Kindle Format Now also available in PDF at Hint: Kent is the Technical Editor
    44. 44. Kscope Special for LearnDataVault Go to Discount coupons for: Super Charge book DV Implementation course DV using Informatica course
    45. 45. Data Vault References On YouTube: On Facebook:
    46. 46. Contact Information Kent Graziano The Oracle Data Warrior Data Warrior LLC Visit my blog at @KentGraziano Stewart Bryson US Managing Director Rittman Mead @stewartbryson T : +44 (0) 8446 697 995