1. Kerr-McGee Information Management Group
Developing and Deploying Data Warehouse and Business Intelligence Solutions
Kerr-McGee Information Management Group
Skye Brannon Jeff Bridgwater Sarena Sherrard
DW Analyst DW Manager Sr. DW Analyst

2. Who is Kerr-McGee?
Kerr-McGee is an Oklahoma City-based energy and inorganic chemical company with worldwide operations and assets of approximately $10 billion.

3. Agenda Introduction to DW/BI Concepts Extract, Transform & Load (ETL)
Business Intelligence / Reporting
A Day in the Life

4. DW / BI Concepts

5. Information Management Strategy
Structure the systems and data relationships to provide user-friendly customer access to data in order to provide decision-making information.

6. Adding Value to Data

7. Information Pyramid

8. What is a Data Warehouse?
A copy of data from one or more On-line Transaction Processing (OLTP) systems specifically structured for Query, Reporting and Analysis (QRA).
Data is typically at a summarized level to limit the size and complexity of the data warehouse
Data is usually cleansed and merged to create an “apples to apples” comparisons
End-User
Reporting
OLTP
Systems
Data
Warehouse

9. The Idea Behind Data Warehousing
POS
FINANCIALS
INVENTORY
Source Systems
BILLING ?
Data Warehouse
Meaningful
&
Easy
Access
Extract
&
Transform
Data
Information

10. Framework Architecture
Metadata Management
Project Management & Quality Assurance
Source
Systems
External Data
Data
Transformation
Extraction
Cleansing
Integration
Improvement
Operational
Data Store
Warehouse
OLAP
Query
Information
Delivery
Mining
Operations & Systems Management
Datamarts
Enterprise
Reporting

11. Business Intelligence
Sales
Business Activity
Marketing
Service Customers
Manage Inventory
Maintain Accounts
Product Performance
Sales Performance
Customer Behavior
Marketing Performance
Inventory Monitoring
Financial Performance
Business Intelligence
Integrated
Meaningful
Consistent
Validated
Easy to Use
Leveragable
Timely
Data
Information

12. K-M As-Is Corp. Chemical O&G Issues Multiple Versions of the Truth
Oracle
Financials
Passport
InPower
HR Data
Warehouse
Chemical
Domestic
Oracle
Financials
Production
Operations
Passport
Financial
Operations
Adage
European
Oracle
Financials
Data
Warehouses
Maximo
Chemhouse
Existing
Reporting
Systems
TOLAS
O&G
O&G
Data
Warehouse
Tobin
Novistar
Energy
Financials
Issues
Multiple Versions of the Truth
Different definitions for similar data
Multiple Reporting Tools and Reports
Impacts Performance of Oracle Financials
DFW
PREMAS
P2000
Aberdeen
Oracle
Financials
Merak
Others
Intl.
Systems
Aberdeen
Data
Warehouse

13. STANDARDIZE, CONSOLIDATE, MINIMIZE, & SIMPLIFY
Corp.
HR Data
Warehouse
K-M To-Be
Oracle
Financials
Phased Out
Passport?
Peoplesoft
Production
Operations
Budget &
Forecasting
Application
Chemical
“Centralized”
Data Warehouse(s)
Passport
Domestic
Oracle
Financials
Financial
Operations
Consolidated
Analysis & Reporting Solution
(Cognos
Business Intelligence)
Adage
Data
Warehouses
European
Oracle
Financials
Maximo
Existing
Reporting
Systems
Dashboards
& KPI Mgmt
TOLAS
Chemhouse
Consolidated
Reporting
Systems
O&G
Novistar
Energy
Benefits
Single Version of the
Truth
Business Intelligence environment leads to Timely Analysis &
Reporting
Consolidated Tool
Enables Multiple
Economies of Scale
- Massaging & Distribution
- Desktop/Maintenance
- Transaction System Load’
Tobin
DFW
O&G
Data
Warehouse
Possibly
Phased Out or Integrated
PREMAS
P2000
Aberdeen
Oracle
Financials
Aberdeen
Data
Warehouse
Merak
Possibly
Phased Out or Integrated
Intl.
Systems
Others
STANDARDIZE, CONSOLIDATE, MINIMIZE, & SIMPLIFY

14. Data Warehouse Roles
Manager Planning and management of entire product or project lifecycle; May assist in ETL & BI Interface design and development
Data Warehouse Architect – Applies knowledge of technology options, platforms, and design techniques across product and project lifecycle; responsible for design of overall warehouse process
ETL Specialist – Analysis and design of extraction, transformation, and loading strategy; development of ETL scripts and procedures
Business Intelligence Specialist – Design and development of multidimensional-cubes & reports; performance and tuning of chosen technologies
Web Interface Specialist – Design and development of application interface elements; coordinates interfaces between application components

15. ETL

16. Project Management & Quality Assurance Operations & Systems Management
Data Extraction and Transformation
Metadata Management
Data Extraction and Transformation
Applying business rules to turn data into useable information
Clean up and standardization of consumers, vendors, products, etc.
Integration of disparate internal and external data
Can be 70% - 80% of effort
Issues
- Can be difficult and time consuming to define business rules
- Extraction tools automate only the more simple tasks
Plan/Forecast/ Analysis
Data
Extract
Cleansing
and
Integration
Process
External Data
OLAP
Query
Global / Dept/ Business Unit Summary and
Analysis
Datamarts
Data
Visualization
Data
Mining
Executive
Information
Systems
Data
Transformation
Operational
Data Store
Data
Warehouse
Source
Systems
Information
Analysis
Project Management & Quality Assurance
Operations & Systems Management

17. + + = ETL Challenges Data Volume Source Inclusion Extract Timing
Warehouse
Complexity
Warehouse Complexity
Destructive vs. Incremental Loads
Integration (mergers/acquisitions)
Data integration (consolidation of information)
Process integration (consolidation of processes)
Smaller windows of opportunity
Make decision in a shorter period of time due to competitive, global market
Global marketplace (DW timing updates)
High-profile e-Business initiatives
Satisfying requirements
No ONE correct answer/solution

18. ETL - The “Heavy Lifting”
Challenge to develop efficient, consistent methods of gathering and cleansing heterogeneous data
Capture and load of data from multiple source systems (both internal and external)
Integrates data into a single source
Cross-system mapping to standard identifiers (surrogate keys)
Aggregation for information delivery and BI initiatives

19. ETL Tools - Only Half the Story
Half the story: ETL Tools Extract, Transform, and Load data
Transport data between sources and targets
Document data element changes (metadata)
Administer run-time processes and operations
Scheduling
Error management
Audit logs
Statistics

20. ETL Tools – Core Components
Databases/Files
Metadata Import/Export
Target Adapters
Extract
Runtime Metadata Services
Metadata Repository
Transform
Load
Design Manager
Source Adapters
Databases/Files/ Legacy Apps

21. $5,000-$10,000 $250,000 and UP ETL - The Options Software Products
“Homegrown” Solutions
SQL*LOADER, PL/SQL, GATEWAYS & LINKS
Developer-bound
Little cohesion between components
Niche Players (Oracle Warehouse Builder / DataJunction)
Enhanced Scheduling & Logging
Not Multi-Warehouse Oriented
Informatica Powermart
Great UI
Powerful Scheduling & Logging
High Price
Proprietary Transform Language
$5,000-$10,000
$250,000 and UP

22. ETL - The Reality Data Repository Mainframe DBMS ERP RDBMS Oracle
“New” Sources
Flat File
O/S
Scripts
COBOL
Code
3GL
Code
SQL
Scripts
Loader
Utility
PERL
Scripts
Interface
Apps
Data
Repository

23. Informatica Powermart
Repository Manger
Designer
Workflow Manager
Workflow Monitor

24. Business Intelligence / Reporting

25. What is Business Intelligence?
Business Intelligence is the transformation of data into information you can use to drive your business.
There are a number of vendors that have developed Business Intelligence software. Kerr-McGee uses Cognos.

26. Business Intelligence Tools
Metadata Management
Business Intelligence Tools
Combination of applications and tools
Provide analysis, presentation and reporting facilities for users
Tailored to meet diverse needs of executives, mgrs, analysts
Data may reside in ODS, data warehouse or data mart
Issues
How do you choose the right tool or tools?
Plan/Forecast/ Analysis
Data
Extract
Cleansing
and
Integration
Process
External Data
Global / Dept/ Business Unit Summary and
Analysis
OLAP
Query
Datamarts
Data
Visualization
Data
Mining
Executive
Information
Systems
Data
Transformation
Operational
Data Store
Data
Warehouse
Source
Systems
Information
Analysis
Project Management & Quality Assurance
Project Management & Quality Assurance
Operations & Systems Management

27. Categorize Information Needs
Highly
Summarized
Moderately
Integrated Operational Data
Executive
Senior Management
Management
Business Analysts
Market Researchers
Financial analysts, product managers, etc..
Business Users
During Requirements Gathering characterize the information access needs of the target audience(s) for the solution. Basic questions:
What business process /activities am I focusing on as part of the scope?
What is the data?
How do people across an organization want to access, view and manipulate it?
What’s the primary audience for the application?
Executive:
top down view of the business
monitoring the overall effectiveness of the organization in predictable ways
Business Analysts:
analyze information from a number of different perspectives
analysis can be aided by ability to view key aspects of a business in a hierarchical fashion
Product: Product Groups, Brands, Products
Geography: Regions, States, Cities
Time: Year, Quarter, Month, Week, Day
Business Users:
Hard copy reports (e.g. customer lists, sales totals, etc. )
Exploratory questions and answers (e.g.. customers in Texas spending > 500 at a store)
Salespersons,
line managers,
administrative staff, etc..

28. Information Delivery Mechanisms
Wireless
Mobile
Operational Trends
Web or
C/S
Delivery Mechanism Considerations
Integrated with Operations?
Detailed Reporting only?
Real-time or based on a Periodic Business Cycle (Financials)
Tethered or ‘disconnected’?
C/S
Web
Wireless
Predefined
Summaries
Data
Visualization
Operational Trends
Web or
C/S
Specialized
Algorithms
Directed Analysis
Determine appropriate delivery mechanisms to satisfy information access needs.
Standardized Reporting:
regularly scheduled, monthly, quarterly
parameter driven on demand (e.g.. enter date range, division, etc..)
example: promotion reports, contributing zips
Adhoc Queries
unplanned information access to support unexpected business questions
example: generate a report of all sweater buyers in xxx stores
User Directed Analysis
analysis of key aspects of a business along natural business hierarchies (product, geography, time, etc.. )
looking for exceptions & anomalies, the process is largely user driven
example: J&J product tracking by customer over time
Specialized Algorithms
uncovering hidden relationships & correlations between different pieces of data
far less user directed, the idea is to use algorithms to help identify key facts
example: discovering correlations between doctors and types of procedures
Executive
drawing pretty pictures and charts of interesting key high level measures
(in millions)
1998
1999
2000
2001
2002
Net Revenues
$x,xxx
Net income
xxx
x,xxx
Earnings per share
x.xx
Return on net revenues
xx%
Cash & s/t investments
$xxx
Total Assets
Shareholder Equity
Operational Trends
Web or
C/S
Standardized
Operational
Reporting
Ad-hoc
Queries

29. B.I. Infrastructure
Production environment consists of 6 load balanced servers within a DMZ. These include;
A Web Server (Primary and Secondary)
A Reports Server (Primary and Secondary, NT today SUN Enterprise tomorrow)
An Application Server (Primary and Secondary)
Outside of the DMZ the actual warehouse resides on a cluster of Sun Enterprise 3500 servers attached to a 100GB EMC RAID Array.
Keep in mind that duplicate environments for Development, Test and Production were created.

30. Access Manager – (Security) Upfront – (Portal – http:/intranet/kmbi)
All things Cognos
Cognos is a vendor. The suite of applications we’ve bought and use from Cognos are:
Access Manager – (Security)
Upfront – (Portal –
PowerPlay – (reports/cubes)
Impromptu – (Web based PDF reports)
NoticeCast – (conditional report notifications)
*Visualizer – (graphic depictions of data warehouse/cube information)
*What we will cover.

31. Terminology
Cube - A multidimensional way to analyze information, designed to provide quick answers to the who, what, why, when, and where business questions.
Drill Down - Going from a summarized view to a more detailed view of information within the same cube
Drill Across - Linking data from One Subject Area to Another (General Ledger to Accounts Payable)
Drill Through - Linking to source data using selected filters
Powerplay Web - On-Line Analysis Tool for cubes (slice/dice, drill down, drill across & drill through)
Newsbox -A web based folder used to store views of data (reports). Every KMBI user has their own personal newsbox.

32. Cognos - Upfront
Upfront - Portal Management

33. Cognos - PowerPlay
PowerPlay – web reports/slicing and dicing/data analysis, based on cubes.
More Information on Cognos website:

34. Cognos - Impromptu
Impromptu – printable reports (in PDF) that may/or may not be produced with prompts for filtered information.

35. Cognos - Visualizer
Visualizer – interactive graphic depictions of data warehouse/cube information

36. Developing Visualizations
Initial Project meeting should include:
Client - gives input on look and feel, data requirements, timelines
Project Manager – ensures project is feasible within budget and time restraints at the onset and through out the project.
Data Warehouse Architect – ensures all the needed data is in the data warehouse.
Business Intelligence Specialist (cube builder) – ensures all the needed data is in the cube, in the correct format
Web Interface Specialist (visualization builder) – works with cube builder and client to established look and feel, navigation, chart styles, etc..

39. Day in the Life

40. Typical Day