1 Brett Hanes 30 March 2007 Data Warehousing & Business Intelligence 30 March 2007 Brett Hanes

2 30 March 2007 Agenda Overview Data Warehousing Definition & Purpose Varieties General Architecture Modeling More Information Business Intelligence Definition & Purpose Common Components How It All Works Together Why Is It Useful? How To Convince The Business Summary

3 Brett Hanes 30 March 2007 Data Warehousing (DW) Definition A subject-oriented, integrated & non-volatile database updated on a typically rhythmic cycle from an enterprise’s various transaction databases. Purpose Accumulate data from disparate data sources for querying purposes Separate reporting and analysis operations from transaction systems to maximize the performance of both Commonly very large repositories that house historical data

4 Brett Hanes 30 March 2007 Common Data Warehouse Components Staging Area A preparatory repository where transaction data can be transformed for use in the data warehouse Data Mart Traditional dimensionally modeled set of dimension and fact tables Per Kimball, a data warehouse is the union of a set of data marts Operational Data Store (ODS) Modeled to support near real-time reporting needs Contains traits of both relational and dimensional modeling techniques

5 Brett Hanes 30 March 2007 Data Warehouse Modeling Data warehouses typically use a denormalized method called dimensional modeling made up of the following components: Dimension An entity defined in its entirety with a single primary key Examples: Customer, Product, Sales Force, Calendar Fact Details (often numerical) regarding a set of dimensions Example: Order Details

6 Brett Hanes 30 March 2007 Data Flow from Transaction to Warehouse Complex Structure Necessary for Accurate Transactions Simplified Structure Necessary for Fast, Powerful Reports 1 - Data Input via Applications to transaction databases 2 - Data transfer from transaction system to data warehouse via Extract- Transform-Load (ETL) Tool (i.e. Informatica) 3 - Data Output via Business Intelligence Tool (i.e. Cognos, Business Objects, Hyperion) Separation of Transactions and Reporting Improves Performance and Enhances Capabilities

7 Brett Hanes 30 March 2007 Learning More About Data Warehousing Pre-eminent Data Warehousing Minds –Bill Inmon -> Normalization Building the Data Warehouse Corporate Information Factory –Ralph Kimball -> Dimensional The Data Warehouse Lifecycle Toolkit The Data Warehouse Toolkit Word is they don’t really get along

8 Brett Hanes 30 March 2007 Business Intelligence Software Definition A set of tools that allow users to access enterprise data via reports, Online Analytical Processing (OLAP) cubes, graphs/charts, ad-hoc queries and dashboards Purpose Allow users to view the data from all levels of the enterprise Provide users with information necessary to make timely, well-informed business decisions The tools must be easy for the end user to understand and manipulate

9 Brett Hanes 30 March 2007 Some Components In The BI Toolkit Reports (Example)Example Commonly needed data can be structured in a set of canned reports made available to large numbers of users Flexibility can be given to users through ad-hoc querying and filters Cubes (Example)Example Multi-dimensional, allowing the user the view the data from multiple angles Interactive, giving the user the ability to change what is viewable on the fly

10 Brett Hanes 30 March 2007 Some Components In The BI Toolkit Charts & Graphs (Example)Example Graphical Representation of data Commonly used in presentations and statistical analysis Dashboards (Example)Example Actively updating graphical displays that provides business users with updates on key metrics Some dashboards provide drill through capability, allowing users to start with summary data and dive in to the details

11 Brett Hanes 30 March 2007 How It All Works Together Extract Transform Load Data Input OLTP ATRRS OLTP RECBASS OLTP AIMSPC RATSS RFMSS Other Possible Data Sources Disparate Data Sources TIMS DW Single Reporting Repository Real-time Dashboards Static and Ad-hoc Reporting Graphical Data Analysis

12 Brett Hanes 30 March 2007 Why Is It Useful? ODS DW The data transmitted from the engine in flight can alert a service team of an engine component in need of repair so they can meet the plane at the gate. Engineers can analyze the data to find ways of designing engine components with longer life spans.

13 Brett Hanes 30 March 2007 Convincing The Business Consider the Previous Example –Having a team waiting at the gate to service an engine reduces flight delays –Engineering analysis helps create higher quality engines that: Requires less servicing Stay on wing longer In Other Words….You Save $$$$$$$$$!!!!! Learn to speak the language of the business users…Understand what is important to them

14 Brett Hanes 30 March 2007 Keys To Success Sponsorship High level endorsement is essential to ensuring you have the authority to drive the effort Funding You have to spend money to save/make money Time This can be a years long effort to implement Maintenance is ever-present Central Governance Without strict governance over components of your enterprise data warehouse, you risk stove piping

15 Brett Hanes 30 March 2007 Summary Data is Key Whether coming in or going out, data is the foundation of all business applications and should be structured to properly meet the need Solutions are Complex There are many components to a good BI strategy…and they all have to work Diligence Required Data will change Technology will change Be assured…user requirements will change

16 Brett Hanes 30 March 2007 Questions?

17 Brett Hanes 30 March 2007 Appendix

18 Brett Hanes 30 March 2007 Report Example

19 Brett Hanes 30 March 2007 Cube Example Dimensions and facts can be dragged and dropped on the to display to view the data in different ways

20 Brett Hanes 30 March 2007 Chart/Graph Example

21 Brett Hanes 30 March 2007 Dashboard Example