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Business Intelligence What is BI? • Business Intelligence is a broad category of applications and technologies for gathering, storing, analyzing, and providing access to data to help managers make better business decisions BI Evolution Group Memory Corporate Intranets & Decision Support Portals Extranets & Interenterprise portals E-Commerce & Click Stream Analysis Business Intelligence Business Intelligence Technologies Increasing potential to support business decisions Decision Making Data Presentation Visualization Techniques Data Mining Information discovery End User Business Analyst Data Analyst Data Exploration OLAP, DSS, EIS, Querying and Reporting Data Warehouses / Data Marts DB Admin Data Sources Paper, Files, Information Providers, Database Systems, OLTP Business Processes (E.g. Banking) (agreement with a credit card) (grant a loan) (transaction on bank account decisional processes management processes operational processes DSS vs. EIS • Decision Support Systems (DSS) and Executive Information Systems (EIS): information systems designed to help managers in making decisions. • Different, yet interrelated applications • A DSS focuses on a particular decision, whereas an EIS provides a much wider range of information (e.g., information on financials, on production history, and on external events). • DSSs appeared in the 1970s • EISs appeared in the 1980s. Where does an EIS or DSS get its data? • The EISs and DSSs often lacked a strong database component. • Most organizational information gathering was (and is) directed to maintaining current (preferably on-line) information about individual transactions and customers. • Managerial decision making requires consideration of the past and the future, not just the present. • New databases, called data warehouses, were created specifically for analytic use Data Warehousing • The process of collecting and storing large quantities of historical data from different sources in one CENTRAL location • Data mining is the analysis of data to establish relationships and identify patterns A Data Warehouse is ... A data warehouse is a – subject-oriented, – integrated, – time-variant, and – nonvolatile collection of data in support of management’s decisions … subject-oriented ... • The data in the warehouse is defined and organized in business terms, and is grouped under business-oriented subject headings, such as – customers – products – sales rather than individual transactions. • Normalization is not relevant. … integrated ... • The data warehouse contents are defined such that they are valid across the enterprise and its operational and external data sources Data warehouse Operational systems The data in the warehouse should be clean validated properly integrated … time-variant ... • All data in the data warehouse is time-stamped at time of entry into the warehouse or when it is summarized within the warehouse. • This chronological recording of data provides historical and trend analysis possibilities. • On the contrary, operational data is overwritten, since past values are not of interests. … nonvolatile ... • Once loaded into the data warehouse, the data is not updated. • Data acts as a stable resource for consistent reporting and comparative analysis. • This is different to operational data that is updated (inserted, deleted, modified). Which Data in the Warehouse? • A data warehouse contains five types of data: – Current detail data – Old detail data – Lightly summarized data – Highly summarized data – Metadata How does data get into a data warehouse? Checking Account System Jane Doe (name) Female (gender) Bounced check #145 on 1/5/95 Opened account 1994 Savings Account System Jane Doe F (gender) Opened account 1992 Investment Account System Jane Doe Owns 25 Shares Exxon Opened account 1995 Operational data Customer Jane Doe Female Bounced check #145 Married Owns 25 Shares Exxon Customer since 1992 data warehouse Cost and Size of a Data Warehouse • Data warehouses are expensive undertakings (mean cost: $2.2 million). • Since a data warehouse is designed for the enterprise it has a typical storage size running from 50 Gb to over a Terabite. The Data Mart • A lower-cost, scaled-down version of the data warehouse designed for the strategic business unit (SBU) or department level. • An excellent first step for many organizations. • Main problem: data marts often differ from department to department. • Two approaches: – data marts enterprise-wide system – data warehouse data marts An Architecture for Data Warehousing metadata EIS DSS external sources . OLAP data warehouse data mining query operational databases data mart On-Line Analytical Processing (OLAP) • Decision support software that allows the user to quickly analyze information that has been summarized into multidimensional views and hierarchies. • E.g., OLAP tools can be used to perform trend analysis on sales and financial information. They enable users to drill down into masses of sales statistics in order to isolate products that are the most volatile. On-Line Analytical Processing (OLAP) Market • Basic idea: users should be able to manipulate enterprise data models across many dimensions to understand changes that are occurring. • Data used in OLAP should be in the form of a multi-dimensional cube. Product Dimensional Hierarchies • Each dimension can have a hierarchy Year Country Type of product Month State Product Week City Item Day Store Star Schema Fact Table Market Dimension STORE KEY Store Desc. City State District ID District Desc. Region ID Region Desc. Regional Mgr. Level STORE KEY PRODUCT KEY PERIOD KEY Dollars Units Price Product Dimension PRODUCT KEY Product Desc. Brand Color Size Manufacturer Time Dimension PERIOD KEY Period Desc. Year Quarter Month Day Journal Question 8 Do you think that business managers in Doha are embracing Business Intelligence applications? Why or why not?