UNT BCIS 4660 - Lecture06a_MarakasChap1_Spring2012

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Chapter 1: Introduction to Data Mining, Warehousing, and VisualizationObjectives1-1: The Modern Data Warehouse1-2: Data Warehouse Roles and StructuresElements of a DWPosition of the Data Warehouse Within the Organization – Figure 1-2Data Mining Example Service Quality vs. TrainingPowerPoint PresentationSlide 131-4: The Cost of DWSlide 151-5: Data Mining: Farmers and Explorers1-6: Foundations of Data Mining1-6 & -7: The Foundations of Data MiningData Mining – A General ApproachA General Approach (continued)The Data Warehouse and Data MiningVolumes of Data – The Biggest Challenge1.9: Foundations of Data Visualization [DV]Dr. John Snow used a map to show the source of cholera was a water pump, thus proving the disease was water borne.DV: Opportunity and TimingSlide 31Slide 33DV & DM: Future Success DriversThe End11Modern Data Warehousing, Mining & Visualization, 2003, George MarakasChapter 1: Introduction to Data Mining, Warehousing, and VisualizationModern Data Warehousing, Mining, and Visualization: Core Concepts by George M. MarakasSpring 201221Modern Data Warehousing, Mining & Visualization, 2003, George MarakasObjectivesWhat is the purpose and motivation for developing a Data Warehouse (DW)?Position of DW within IT infrastructureRelationship between DW and business data martWhat can a DW do?Foundations for Data MiningSteps in a typical Data mining projectWhat is a “Correlation”? KEY CONCEPTHistory of Data Visualization vis-à-vis DW31Modern Data Warehousing, Mining & Visualization, 2003, George Marakas1-1: The Modern Data WarehouseA data warehouse is a copy of transaction data specifically structured for querying, analysis and reportingNote that the data warehouse contains a copy of the transactions. These are not updated or changed later by the transaction system.Also note that this data is specially structured, and may have been transformed when it was placed in the warehouse41Modern Data Warehousing, Mining & Visualization, 2003, George Marakas1-2: Data Warehouse Roles and StructuresThe DW has the following primary functions:It is a direct reflection of the business rules of the enterprise.It is the collection point for strategic information.It is the historical store of strategic information.It is the source of information later delivered to data marts.It is the source of stable data regardless of how the business processes may change.51Modern Data Warehousing, Mining & Visualization, 2003, George MarakasElements of a DWExtractTransformStore[ETS]61Modern Data Warehousing, Mining & Visualization, 2003, George MarakasPosition of the Data Warehouse Within the Organization – Figure 1-2111Modern Data Warehousing, Mining & Visualization, 2003, George MarakasData Mining ExampleService Quality vs. TrainingCourtesy: MicroStrategy (2005)121Modern Data Warehousing, Mining & Visualization, 2003, George MarakasSales Analysis-Determine real-time product sales to make vital pricing and distribution decisions. -Analyze historical product sales to determine success or failure attributes. -Evaluate successful products and determine key success factors. -Use corporate data to understand the margin as well as the revenue implications of a decision.-Rapidly identify a preferred customer segments based on revenue and margin. -Quickly isolate past preferred customers who no longer buy. -Identify daily what product is in the manufacturing and distribution pipeline. -Instantly determine which salespeople are performing, on both a revenue and margin basis, and which are behind. Financial Analysis-Compare actual to budgets on an annual, monthly and month-to-date basis. -Review past cash flow trends and forecast future needs. -Identify and analyze key expense generators.-Instantly generate a current set of key financial ratios and indicators. -Receive near-real-time, interactive financial statements. Human Resource Analysis-Evaluate trends in benefit program use. -Identify the wage and benefits costs to determine company-wide variation. -Review compliance levels for EEOC and other regulated activities.Other Areas-Warehouses have also been applied to areas such as: logistics, inventory, purchasing, detailed transaction analysis and load balancing. Examples of Common DW ApplicationsTable 1-1131Modern Data Warehousing, Mining & Visualization, 2003, George MarakasTable 1-2Costs-Hardware, software, development personnel and consultant costs.-Operational costs like ongoing systems maintenance. -Benefits Added Revenue-Will the new (business objective) process generate new customers (what is the estimated value?) -Will the new (business objective) process increase the buying propensity of existing customers (by how much?) -Is the new process necessary to ensure that the competition doesn't offer a demanded service that you can't match? Reduced costs-What costs of current systems will be eliminated? -Is the new process intended to make some operation more efficient? If so, how and what is the dollar value?Comparison of Typical DW Costs and Benefits141Modern Data Warehousing, Mining & Visualization, 2003, George Marakas1-4: The Cost of DWExpenditures can be categorized as one-time initial costs or as recurring, ongoing costs.The initial costs can further be identified as for hardware or software.Expenditures can also be categorized as capital costs (associated with acquisition of the warehouse) or as operational costs (associated with running and maintaining the warehouse)Cost of a Data Warehouse:Rule of Thumb: $1 million per 1 Terabyte of data151Modern Data Warehousing, Mining & Visualization, 2003, George MarakasRecurring Costs One-Time CostsCapital-Hardware maintenance-Software maintenance-Terminal analysis-MiddlewareHardware Software-Disk DBMS-CPU Terminal analysis-Network -Terminal Analysis Middleware Log utility Processing Metadata InfrastructureOperational-Ongoing refreshment-Integration transformation-Data model maintenance-Record identification maintenance-Metadata infrastructure maintenance-Archival of data-Data aging within the DW-Integration/transformation processing specification-Metadata infrastructure population-System of record definition-Data dictionary language definition-Network transfer definition-CASE/Repository interface-Initial data warehouse


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UNT BCIS 4660 - Lecture06a_MarakasChap1_Spring2012

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