unit ii business analysis cs2032 data warehousing and data mining

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  • Slide 1
  • UNIT II BUSINESS ANALYSIS CS2032 DATA WAREHOUSING AND DATA MINING
  • Slide 2
  • Contents Reporting and Query tools and Applications Tool Categories The Need for Applications Cognos Impromptu Online Analytical Processing (OLAP) Need Multidimensional Data Model OLAP Guidelines Multidimensional versus Multirelational OLAP Categories of Tools OLAP Tools and the Internet
  • Slide 3
  • Reporting and Query Tools and Applications Tool Categories Reporting Tools Managed Query Tools Executive Information System Tools OLAP Tools Data Mining Tools The Need for Applications Cognos Impromtu Applications PowerBuilder Forte Information Builder
  • Slide 4
  • Reporting Tools Production Reporting Tools Let companies generate regular operational reports Support high volume batch jobs Calculating and Printing Paychecks(3GL) COBOL, Information Builders, Inc.s Focus(4GL) MITIs SQR(High-end Client/Server Tools) Desktop Report Writers Let users design and run reports Graphical Interfaces and Built-in charting functions Crystal Reports, Actuate Reporting System, IQ objects
  • Slide 5
  • Managed Query Tools Shield end users from the complexities of SQL and database structures Meta layer Support asynchronous query execution Integrate with web servers Embed OLAP and Data Mining Features
  • Slide 6
  • Executive Information System Tools Predate report writers and managed query tools First deployed on Mainframes Allow to build customized, graphical decision support applications Gives managers and executives a high level view of business and access to external sources Eg: Pilot Software, Forest and Trees, Comshare, Oracles Express Analyzer
  • Slide 7
  • OLAP Tools Provide and intuitive way to view corporate data Aggregate data along common business objects Users can drill down, across, or up levels in each dimension
  • Slide 8
  • Data Mining Tools User variety of statistical and artificial-intelligence algorithms Analyze the correlation of variables in the data and ferret out interesting patterns and relationships to investigate Example IBMs Intelligent Miner DataMind Pilots Discovery Server Offers simple UIs plug in directly to existing OLAP
  • Slide 9
  • The Need for Applications Access Types to the data Simple tabular from reporting Ad hoc user-specified queries Predefined repeatable queries Complex queries Ranking Multivariable analysis Time series analysis Data visualization, graphing, charting, and pivoting Complex textual search Statistical analysis
  • Slide 10
  • Cognos Impromptu Overview The impromptu Information Catalog Object-oriented architecture Reporting Impromptu Request Server Supported Databases
  • Slide 11
  • Cognos Impromtu: Overview Enterprise solution for interactive database reporting Object oriented architecture Ensures control and administrative consistency across all users and reports GUI Database reporting tool Supports single user reporting / multi users reporting
  • Slide 12
  • Cognos Impromtu: Information Catalog LAN based repository of business knowledge and data access rules Insulates users from db technical aspects Protects database Presents the database in a easy way Administrators are free to organize database items
  • Slide 13
  • Cognos Impromtu: OO Architecture Drives inheritance based administration and distributed catalogs Governors Activities of Governors Query activity Processing location Database connections Reporting permissions User profiles Client/Server Balancing Database Transactions Security by value Filed and table security
  • Slide 14
  • Cognos Impromtu: Reporting Picklists and prompts Custom templates Exception reporting Conditional filters Conditional highlighting Conditional display Interactive reporting Frames List frame Form frame Cross-tab frame Chart frame Text Frame Picture Frame OLE Frame
  • Slide 15
  • Cognos Impromtu: Request Server Allows client to off-load the query process to the server Scheduling regular and recurring standard reports Reducing network traffic Runs on HP/UX 9.X, IBM AIX 4.X, Sun Solaris 2.4 Support data maintain in ORACLE 7.x and SYBASE System 10/11
  • Slide 16
  • On-Line Analytical Processing(OLAP)(1) Need for OLAP Multidimensional Data Model OLAP Guidelines Multidimensional versus Multirelational OLAP Categorization of OLAP Tools MOLAP ROLAP Managed Query Environment(MQE)
  • Slide 17
  • On-Line Analytical Processing(OLAP)(2) State of the Market Cognos PowerPlay IBI FOCUS Fusion Pilot Software OLAP Tools and the Internet
  • Slide 18
  • OLAP
  • Slide 19
  • Slide 20
  • Multidimensional Data Model Viewing data as in a cube
  • Slide 21
  • OLAP Guidelines 1. Multidimensional conceptual view 2. Transparency 3. Accessibility 4. Consistent reporting performance 5. Client/server architecture 6. Generic dimensionality 7. Dynamic sparse matrix handling 8. Multiuser support 9. Unrestricted cross-dimensional operations
  • Slide 22
  • Categorization of OLAP Tools MOLAP ROLAP
  • Slide 23
  • MOLAP
  • Slide 24
  • ROLAP
  • Slide 25
  • State of the Market Cognos PowerPlay IBI FOCUS Fusion Pilot Software
  • Slide 26
  • OLAP Tools and the Internet
  • Slide 27