Chris Royle (RL Polk) & William Both (Capgemini) Oracle Open World San Francisco, CA, 5 Oct 2011

Competitive Advantage w/ Oracle Business Intelligence Enterprise Edition 11g/Oracle Exadata

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2 © 2011 Capgemini. All rights reserved.

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Discussion Topics § Polk introduction § Automotive industry intelligence solution utilizing OBI 11g

§ Key implementation components and lessons learned

§ Addressing performance with Exadata

§ Polk’s experience with Exalytics

§ Questions

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Automotive Data and Marketing Solutions Leader

Company Overview

•  1870—R. L. Polk & Co. founded

•  1921—Motor Statistical Operations launched

•  1965—Adds monthly statistics on motorcycles, RVs, commercial trailers, boats and business aircraft

•  1971—Overseas expansion

•  1999—CarFax Ownership

•  2000—Focus on automotive only

•  2003—PolkInsight launched

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Depth of Automotive Data Polk manages a complex set of online vehicle data to support the automotive industry as our core business

§  2.6 Billion Transactions §  Titles §  Registrations §  Sales §  Vehicle Manufacturers §  Financial Institutions

§  500 Million Unique Vehicles §  Passenger §  Commercial

§  Over 118 Million Households, 195 Million Individuals

§  Compiled from 31 different public and self-reported data sources

§  Over 460 Variables of Consumer Data

§  Demographics §  Lifestyles §  Vehicle Intenders §  Internet Shopping

§  Over 17 Million Businesses §  35 million vehicles §  Compiled from 39 different public and

self-reported data source

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Our Customers

§ All global OEMs (incl. emerging) § Dealers / dealer groups § Aftermarket companies § Finance and insurance companies § Advertising agencies § Media companies § Consulting organizations § Government agencies §  Investment firms § Market research firms § Web portals § Search engines

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Our Business is Providing BI Solutions as a Service

Market Reporting

Vehicle & Consume

r Data

§  Sales and Registration §  Loyalty & Analytics §  Forecasting §  Aftermarket §  Commercial §  Network Management

"  Analyze Market Position "  Pin-Point Key Markets "  Identify Trending "  Determine Opportunities "  Illustrate Competitive Threats

PolkInsight, Polk’s flagship product, is the industry standard for answering questions about automotive market activity

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§ Interpret new, used registration, VIO and OEM sales statistics

§ Unique customized definitions of geography and vehicle segments

§ Simple metrics sliced many ways – the vehicle was registered…..

o  By who -- Age, Income, ethnicity, …. o Where -- Do they live, was the dealer, …. o Which -- Vehicle, engine, body style, transmission, ….. o  For what purpose -- Retail, fleet, government, rental, ….

§ Infinitely variable drill path

PolkInsight Product Overview

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§ Oracle 4 node BI application: Discoverer, Oracle Reports, customer query tool integrated through Oracle Portal

§ 6 node (4 dual-core CPUs, 64GB each) 10G RAC/RH4 cluster

§ 2TB warehouse – 4 shared fact tables with a combined total of 1 Billion + rows

PolkInsight Architecture – Before OBI and Exadata

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Business Intelligence Challenges

§ Users were becoming impatient with the usability of our toolset •  Make it as easy as Excel

§ Users want to see traditionally disparate subject areas on a single dashboard – data mash-ups •  How does the data correlate?

§ Users expect ‘Google’ performance •  Why do I have to wait 30 seconds?

§ Delivery to extended devices •  I want it on my iPad

§  IT resources and activities were too involved in the analytical process •  I have to pay for that change?

Polk selected Oracle’s Exadata and Oracle Business Intelligence (OBI) to help evolve and improve PolkInsight

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Selecting Our Business Intelligence Software Provider

Custom ?

Know what is important to your users, now and tomorrow. Do multiple PoCs – prove it works!

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Implementation Highlights •  Clear requirements •  Manageable scope •  Support from BI Consulting

Group (now Capgemini)

PolkInsight 3.0 Portal

Exadata

OBI 11g

Oracle Discover, Reports

Oracle Map Viewer

PolkInsight 3.0

Customers

Polk Advisors

Architecture Highlights •  Highly available, clustered

environment •  Custom flex portal

OBIEE implemented and integrated in 3 months

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PolkInsight 3.0 Portal with OBI Dashboard Integration

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Engagement Objectives

§  PolkInsight had been a Customer Delivered solution based upon Oracle Discoverer •  Desire to Maintain similar Report Developer Interface to Discoverer Data Layout •  Not an OBIEE 10g Upgrade, rather a first time implementation •  One of the First Corporations to Implement OBIEE 11g •  Build 11g RPD Using BICG/Capgemini Best Practices

§  Utilize Existing Custom Data Warehouse (PolkInsight) •  Minimize Physical Data Model modifications

§  Create Generic Template Dashboard •  Utilizing BICG/Capgemini Best Practices for Report and Dashboard Design •  Provide Enhancements to Prior reporting capabilities

§  Train Polk Advisors in use of Answers to build Customer Specific Dashboards •  Each Advisor is responsible for Several Auto Manufacturers (Polk Customers) •  Each Customer Specific Dashboard was tailored to specific Customer needs

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Implementation

§  Actual Design and Build is not overly difficult, rather it is complex and very meticulous work

§  Customer Involvement Earlier was Critical to Success •  Project Team 80/20 Mix •  Polk Advisors Trained and developed Customer facing dashboards (User Ownership)

§  Utilized BICG/Capgemini Best Practices for RPD Design §  Introduce MoM, QoQ and YoY reporting functionality by creating Time Series

Aliases •  MAGO •  QAGO •  YAGO

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Polk Logical Data Model

§  Four Key Facts •  New Car Registrations •  Used Car Registrations •  Sales Figures (from each Manufacturer) •  Vehicles In Operation (VIO)

§  Principle KPI is Counts of Vehicles §  Several Common Dimensions associated with each Fact §  Limited Dimensions that are specific to only one or another Star §  Data Model Enhancement

•  Addition of a Standard W_MONTH_D table •  Modifications as needed to allow Facts to leverage the Intelligent Key

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200 + Tables

New & Used Sales Facts 4

Category 23 Geography 38 64

Make & Model 25 21 Parameter 8 Sale Type 14

Ethnic Code 1 1 Misc 9 Total 108 100

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Logical Data Model Example

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Logical Data Model Example

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Logical Data Model Example

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Physical Layer Best Practices Use of and Naming of Aliases

Sole Metric

Time Series

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Physical Joins

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Logical Layer Joins

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Logical Layer Best Practices

§  Dimensional Hierarchy for Each Logical Dimension Table §  Accurately defined Primary Keys §  Content Levels Set for each Dimension

•  Detail level for Joined •  Total level for Un-Related

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Logical Dimension Tables §  Frequently multiple Logical Table Sources

§  Both Common as well as Customer Specific flavors or Dimension tables

§  Simple PKs

§  Minimal need for Custom Fields

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Customer Specific Dimensional Hierarchies §  Each Logical Table has a separate

Dimensional Hierarchy •  Even if it only consists of a Total Level and

a Detail Level

§  Each Customer Specific Hierarchy could differ on Naming conventions as well as number of levels

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Dimensional Hierarchies (Cont) §  Several Cases where Hierarchies had

multiple branches

§  Customer Specific Preferred Drill Paths

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Logical Fact

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Presentation Layer

§  Standardized Naming Convention •  NA •  China

§  Common, Polk Standard Subject Area

§  Customer Specific Subject Areas

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Subject Area

§  Standard Subject Area Layout for each Customer

§  Includes both Common (Generic Polk) and Customer flavors of attributes where appropriate

§  Standardized Field Naming conventions except where Customer has indicated otherwise

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Lessons Learned

§  Security Discussion •  Authentication (Oracle SSO) •  Authorization (LDAP - OBIEE User Groups) •  Data Level (TBD)

§  Caching Strategy •  Comprehensive approach to handle diverse customer profiles beyond initial

implementation •  Purge Strategy

§  Organizational BI Ownership •  Content •  Metadata •  Data •  H/W

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Establishing a Performant Foundation with Exadata

Highlights: §  10x out of the box query improvements §  Less data center space §  Compression resulting in less storage and performance gains

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§ Our Half Rack Exadata server was Delivered July 2010 •  Oracle techs were on site for 3 days •  Configured the server according to our specifications •  Left us with a fully functional system

§ Our Flagship Product (PolkInsight) was in Production by October •  Most of the time was spent testing the upgrade from 10G RAC to 11G RAC •  Our goal was to migrate the database, without trying to leverage Exadata

specific performance features (we are doing that now) •  Other than a dramatic improvement in performance, the migration was

transparent to our customers

§ By January 2011, all of our Customer Facing BI Apps were running on Exadata •  We have decommissioned quite a bit of existing hardware •  We consolidated a number of stand alone databases in the process

Our Experience with Exadata

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End User Report Return Time

§ Out of the box improvement

§ Now optimizing to Exadata strengths •  Index removal •  Materialized Views •  Storage Indexes

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Polk’s Experience with Oracle’s Exalytics

§ Test Pilot Program Overview •  Analysis was performed in Oracle’s lab •  Full copy of Polk’s 2TB production data set, running on an identical

Exadata Half Rack •  The Exalytics box was connected to Exadata through InfiniBand •  Test case were chosen by Polk, targeting underperforming dashboards

and drill paths

§ Performance results •  10.5x average performance gains against Exadata cache misses •  Maximum improvement of 114x on corner case drill paths •  All end user response times within 3 seconds with 87% of all interaction

with less than 2 seconds response time

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Polk’s Feature Findings

§ Exalytics’ summary aggregate advisor •  Analyzes usage patterns •  Builds appropriate aggregate tables in memory or on Exadata •  Admin must run the analysis tool, set parameters and execute the

creation of the aggregate tables •  This is the secret sauce – more analysis required

§ Interactive visualization and data discovery •  No ‘go’ button, new data selector types •  Type ahead dropdowns •  Removal of complete screen refresh in 11.1.1.6

§ New chart types (not available in the beta release) •  Trellis •  Multi panel view and microcharts •  Wheel chart •  Animation

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Business Value

For our customers: §  First to know §  Speed §  Most complete view of the industry §  Easy to be the expert

For Polk: §  Improve customer satisfaction §  Generate and retain business

` Enable better decisions to sell more cars, parts

and services

`

Remain the leading provider in Automotive Intelligence

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Questions?

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Please contact: • Chris Royle Chris.Royle@polk.com • William Both William.Both@capgemini.com • Ron Lewis Ron.Lewis@polk.com

www.capgemini.com

The information contained in this presentation is proprietary. ©2011 Capgemini. All rights reserved