Introduction to BI


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Introduction to BI

  1. 1. Business Intelligence
  2. 2. Business Intelligence <ul><li>Business intelligence (BI) is a broad category of application programs and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining. </li></ul><ul><li>Essentially, exploiting data to make a business more profitable </li></ul>
  3. 3. Harrah’s Entertainment <ul><li>Harrah’s maintains a database that contains data on customer activity slot machines, restaurants and other retail outlets as well as demographic data and gambling habits </li></ul><ul><li>Harrah’s used this data to determine that 26% of gamblers generate 82% of their income and those gamblers were not the high rollers </li></ul><ul><li>From this they generate promotions targeted at specific groups or even specific customers </li></ul>
  4. 4. Meijer <ul><li>Meijer, a regional supermarket, used data mining to determine that certain core items sold in all stores but many other items only sold in some stores </li></ul><ul><li>Meijer tailors store stocks based on this data </li></ul>
  5. 5. Business Intelligence Process
  6. 6. Analysis <ul><li>People analyze the world using mental models </li></ul><ul><li>Mental models are a result of experience, education, etc. but are also constrained by the information available </li></ul><ul><li>BI systems (should) allow free-form acquisition to information so allowing less restrictive mental models </li></ul>
  7. 7. Insight <ul><li>Insight is the product of broad, free-ranging analysis born of questions that only humans can ask and discovery of patterns that only humans can recognize as useful </li></ul><ul><li>BI enables people to ask questions and look for patterns and also allows them to convince others of their insights </li></ul>
  8. 8. Action <ul><li>Well-reasoned, supported analysis allows organizations to act more quickly with confidence so they can be more nimble and responsive to changing conditions </li></ul>
  9. 9. Measurement <ul><li>BI provides for more thorough and timely measurement </li></ul><ul><ul><li>A wider variety of measures taken from a broader range of data sources can be accessed </li></ul></ul><ul><ul><li>Timeliness of measures can be tailored to requirements of each level of management </li></ul></ul>
  10. 10. Manager’s Information Requirements Weekly, monthly or longer Weekly or monthly Hourly or daily Timing Highly summarized KPIs Summarized data with drilldown Detail-level drilldown Concrete Measures Long Term Short Term Day-to-Day Goals Upper Management Middle Management Line Managers
  11. 11. BI Goals <ul><li>Making better decisions faster </li></ul><ul><li>Converting data into information </li></ul><ul><ul><li>Difference between the information that managers require and the large amount of information available has been called the “analysis gap” </li></ul></ul><ul><li>Using a rational approach to management </li></ul>
  12. 12. Increasing the Pace of Decisions Organizations must constantly engage in a process of planning implementing plans, monitoring the status of plans, evaluating results against the plan and reevaluating the plans. One of the goals of BI is to increase the rate at which this cycle can be performed. BI allows managers to monitor, provides information to evaluate and provides information as input for planning. Back
  13. 13. Data – Information - Knowledge
  14. 14. Data <ul><li>Data is a collection of raw value elements or facts used for calculating, reasoning, or measuring. Data may be collected, stored, or processed but not put into a context from which any meaning can be inferred </li></ul>
  15. 15. Data – Information <ul><li>Information is the result of collecting and organizing data in a way that establishes relationships between data items, which thereby provides context and meaning. </li></ul><ul><li>Turning Data into Information </li></ul><ul><ul><li>Process of determining what data can be collected and in what context </li></ul></ul><ul><ul><li>For example, designing a database that models a real world set of entities and relationships among the entities </li></ul></ul><ul><ul><li>Requires technical and some business expertise </li></ul></ul>
  16. 16. Information – Knowledge <ul><li>Knowledge is the concept of understanding information based on recognizing patterns in a way that provides insight to information. </li></ul><ul><li>Turning Information into Knowledge </li></ul><ul><ul><li>Information becomes knowledge when it can be used to address problems confronted by a business </li></ul></ul><ul><ul><li>For example, using analytical systems to find patterns in data that suggest courses of action </li></ul></ul><ul><ul><li>Requires business expertise </li></ul></ul>
  17. 17. From Data to Action Back
  18. 18. Informate <ul><li>Use information to transform work. In the context of enterprise solutions, organizations informate by transforming enterprise solutions data into context rich information and knowledge that supports the unique business analysis and decision-making needs of multiple work forces </li></ul>
  19. 19. End User Access to Data
  20. 20. Informating <ul><li>Organizations and users require experience with a new enterprise system to understand what data is available and to learn what they can do with it </li></ul><ul><li>Often requires adding bolt-ons that provide analytic or DSS capabilities (e.g. Business warehouse or CRM) </li></ul><ul><li>Information portals are often a key component of systems that give users access to data and analytical tools </li></ul>
  21. 21. The “BI Attitude” <ul><li>Seeking objective measurable quantitative facts about the business </li></ul><ul><li>Using organized methods and technologies to analyze the facts </li></ul><ul><li>Inventing and sharing models that explain the cause and effect relationships between operational actions and the effects these have on reaching the goals of the business </li></ul><ul><li>Experimenting with alternative approaches and monitoring feedback on results </li></ul><ul><li>Understanding that people are not always rational </li></ul><ul><li>Running the business based on all these characteristics </li></ul>
  22. 22. Evidence-Based Management <ul><li>EBM is a philosophy of management that: </li></ul><ul><ul><li>Requires that claims be backed-up by supporting data </li></ul></ul><ul><ul><li>Parse underlying logic for faulty cause-and-effect </li></ul></ul><ul><ul><li>Encourage experimentation and exploration </li></ul></ul><ul><ul><li>Reinforce continuous learning </li></ul></ul>
  23. 23. Removing Cognitive Blinders <ul><li>See information – Notice what is happening in the environment </li></ul><ul><li>Seek information – Don’t rely only on the processed and filtered information provided to you </li></ul><ul><li>Use information – Use all relevant data </li></ul><ul><li>Share information – Make sure all team members share their unique information </li></ul>
  24. 24. BI Systems ROI <ul><li>The decision to invest in a BI system is a business decision and should be justified as such </li></ul><ul><li>Costs have to be balanced against the expected value </li></ul><ul><li>The Gartner Group reports that the average ROI from BI projects is 430% </li></ul>
  25. 25. Costs <ul><li>Fixed costs of BI infrastructure </li></ul><ul><ul><li>Servers, storage, software </li></ul></ul><ul><li>Fixed costs of development </li></ul><ul><ul><li>Cleansing data, database development, etc. </li></ul></ul><ul><li>Variable costs of software </li></ul><ul><ul><li>Licenses, training, support </li></ul></ul><ul><li>Variable costs associated with maintenance </li></ul>
  26. 26. Value of Information <ul><li>“Companies that manage their data as a strategic resource and invest in its quality are already pulling ahead in terms of reputation and profitability” </li></ul><ul><ul><li>PricewaterhouseCoopers Global Management Survey, 2003 </li></ul></ul>
  27. 27. Determining the Value of Information <ul><li>Historical Cost </li></ul><ul><ul><li>What did we pay to acquire the information? </li></ul></ul><ul><li>Market Value </li></ul><ul><ul><li>How much would someone pay to acquire the information? </li></ul></ul><ul><li>Utility Value </li></ul><ul><ul><li>What value can we derive from this information? </li></ul></ul>
  28. 28. Factors Affecting Information Value <ul><li>Time value of data </li></ul><ul><ul><li>Data represents a snapshot of reality and so its value degrades over time </li></ul></ul><ul><li>Information as a sharable resource </li></ul><ul><ul><li>Data is not degraded (with a few exceptions) by being shared and its value is often increased by being shared </li></ul></ul><ul><li>Increased value through increased use </li></ul><ul><ul><li>The more it is used the more likely actionable knowledge will be generated </li></ul></ul>
  29. 29. Factors Affecting Information Value <ul><li>Increasing value through quality </li></ul><ul><ul><li>Information of questionable value not only has little value but may have negative value </li></ul></ul><ul><li>Increasing value through merging </li></ul><ul><ul><li>Merging information from disparate sources increases value because of the information contained in the relationships </li></ul></ul><ul><li>Value versus volume </li></ul><ul><ul><li>Value is not necessarily increased and may be decreased by volume </li></ul></ul><ul><ul><li>One can often define an optimum amount of information </li></ul></ul><ul><ul><li>There is a qualitative difference between having lots of data from disparate data sources and having the same amount from the same source </li></ul></ul>
  30. 30. Course Outline <ul><li>Implementation of Business Intelligence Systems </li></ul><ul><li>Analytical Techniques </li></ul><ul><li>Data warehouses </li></ul><ul><ul><li>Data Profiling and Data Quality </li></ul></ul><ul><ul><li>Data Models </li></ul></ul><ul><ul><li>Extraction, Transfer and Loading (ETL) </li></ul></ul><ul><li>SAP Business Warehouse </li></ul>