6Categories of Business Intelligence Tools Reporting toolsQuery tools (data access)On-line analytical reporting (OLAP) toolsAnalytical suitesData mining toolsAnalytical applications
7Evolution of Reporting MainframeClient-ServerMultitierEnterprisereportingBatch orientedIS controlled3GL-basedNot user-specificInflexibleIS intensiveEnd userempoweredReduced ISmanageabilityExpensiveLocalizedEasy to useManageableScalableAccessible
8Oracle Discover 3.1 User Viewer Edition Edition End User Layer Transaction Database or Data WarehouseAdministrationEdition
9Discoverer for the Web View workbooks using a Web browser Business intelligence tool that provides information anywhere and at any timeCost-effective
10Online Analytical Processing (OLAP) ProdProduct mgr.viewRegional mgr.viewSalesMarketTimeAd hoc viewFinancial mgr.view
11Advanced Analytical Tasks Comparative and relative analysisException and trend analysisTime series analysisForecastingWhat-if analysisModelingSimultaneous equations
12Analytical Suites Enterprise business intelligence (EBI) toolsets: - Web-enabled query, reporting, andanalysis tool that runs on a robustapplication server- EBI toolset tightly integrates query,reporting, and analysis capabilities within asingle tool- Shares a common look and feelBusiness portals:- EBI toolset with a Yahoo-like user interface- Flexible repository handles structured andunstructured data objects.
13Data Mining ToolsIdentify patterns and relationships in data that are often useful for building models that aid decision making or predict behaviorData mining uses technologies such as neural networks, rule induction, and clustering to discover relationships in data and make predictions that are hidden, not apparent, or too complex to be extracted using statistical techniques.
14Analytical Applications Packaged analytical application has a predefined:- Extraction feeds and transformationroutines for a specific data source- Data model, application-specificreport templates, and a custom end-user interface.Custom analytic applications are workbenches that enable developers to quickly create analytic applications from coarse-grained components, including user interface widgets, data access and analysis components, and report layouts.
15Definition of Data Mining “ Data mining is the exploration and analysis of large quantities of data in order to discover meaningful patterns, trends, relationships, and rules. ”Data mining is also known as:Knowledge discoveryData surfingData harvesting
16Use of Data Mining Customer profiling Market segmentation Buying pattern affinitiesDatabase marketingCredit scoring and risk analysis
17Functions of Data Mining Discovers facts and data relationshipsFinds patternsDetermines rulesRetains and reuse rulesPresents information to usersMay take many hoursRequires knowledgeable people to analyze the results
18Comparing DSS and Data Mining Queries DSS queries:- Based on prior knowledge andassumptions- User-drivenData mining queries:- Require domain-specific knowledgeto interpret data- User-guided
19Artificial Neural Networks Predictive model that learnsDeveloped from understand of the human brainMultiple regression and other statistical techniques15268374
20Decision Trees Represent decisions Generate rules Classify Annual salary100,000AnnualoutgoingAnnualcredit<10,000>50,000GoodBad
21Other Techniques Genetic algorithms based on evolution theory Statistics such as averages and totalsNearest neighbor to find associationsRules induction applying IF-THEN logicExperiment with different techniques
22AssociatesWhich items are purchased in a retail store at the same time?
23Sequential Patterns What is the likelihood that a customer will buy a product next month, if he buys a related item today?
24Classifications Determine customers’ buying patterns and then find other customers withsimilar attributes that may be targeted fora marketing campaign.
25Modeling Use factors, such as location, number of bedrooms, and square footage, toDetermine the market value of a property
27Summary This lesson covered the following topics: Describing the importance of business intelligenceIdentifying where data mining might be employed in a warehouse environmentIdentifying data mining tools