Download cs2032 data warehousing and data mining

CS2032 DATA WAREHOUSING AND
DATA MINING
UNIT II BUSINESS ANALYSIS
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
Reporting and Query Tools and
Applications
 Tool Categories
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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
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)
 MITI’s 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
Managed Query Tools
 Shield end users from the complexities of SQL and database
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structures
Meta layer
Support asynchronous query execution
Integrate with web servers
Embed OLAP and Data Mining Features
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, Oracle’s
Express Analyzer
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
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
 IBM’s Intelligent Miner
 DataMind
 Pilot’s Discovery Server
 Offers simple UI’s – plug in directly to existing OLAP
The Need for Applications
 Access Types to the data
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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
Cognos Impromptu
 Overview
 The impromptu Information Catalog
 Object-oriented architecture
 Reporting
 Impromptu Request Server
 Supported Databases
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
Cognos Impromtu: Information Catalog
 LAN based repository of business knowledge and data access
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rules
Insulates users from db technical aspects
Protects database
Presents the database in a easy way
Administrators are free to organize database items
Cognos Impromtu: OO Architecture
 Drives inheritance based administration and distributed catalogs
 Governors
 Activities of Governors
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Query activity
Processing location
Database connections
Reporting permissions
User profiles
Client/Server Balancing
Database Transactions
Security by value
Filed and table security
Cognos Impromtu: Reporting
 Picklists and prompts
 Custom templates
 Exception reporting
 Conditional filters
 Conditional highlighting
 Conditional display
 Interactive reporting
 Frames
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List frame
Form frame
Cross-tab frame
Chart frame
Text Frame
Picture Frame
OLE Frame
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
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)
On-Line Analytical Processing(OLAP)(2)
 State of the Market
 Cognos PowerPlay
 IBI FOCUS Fusion
 Pilot Software
 OLAP Tools and the Internet
OLAP
OLAP
Multidimensional Data Model
 Viewing data as in a cube
OLAP Guidelines
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Multidimensional conceptual view
Transparency
Accessibility
Consistent reporting performance
Client/server architecture
Generic dimensionality
Dynamic sparse matrix handling
Multiuser support
Unrestricted cross-dimensional operations
Categorization of OLAP Tools
 MOLAP
 ROLAP
MOLAP
ROLAP
State of the Market
 Cognos PowerPlay
 IBI FOCUS Fusion
 Pilot Software
OLAP Tools and the Internet