MIS: Pichai Takkabutr EAU 2005 3 การกำหนดโครงสร้างและขนาดของระบบข้อมูล File Organization/ Architecture DW/DB/DM/FILE Record/Entity Field/Attribute/Data Element Byte Bits (EBCDIC, ASCII) Binary On, Off Electricity HW Computer Worked Information Management Data Entry/Storage Data Control/Security Data Retrieval/Search การบริหารจัดการ ทรัพยากร สารสนเทศของ องค์กร ISAM DAM SAM queue stack linked list Heap Dictionary tree
MIS: Pichai Takkabutr EAU 2005 4 Differences between the Operational System VS. the Data Warehouse 1.Data in Operational System High volume, detailed High update frequency Record oriented, optimized for performance Current data only Internal data of one application 2. Data in a Data Warehouse Medium volume, summarized Low update frequency (daily, weekly) optimized for queries, accessible for analysis Past and present data Used for several application (OLAP, DSS,...)
MIS: Pichai Takkabutr EAU 2005 5 DATA ARCHITECTURE
MIS: Pichai Takkabutr EAU 2005 6 DATA WAREHOUSE in ORGGANIZATION
MIS: Pichai Takkabutr EAU 2005 7 Physical Structure of Data Warehouses
MIS: Pichai Takkabutr EAU 2005 8 Component of DW
MIS: Pichai Takkabutr EAU 2005 9 Data Extraction & Integration Getting heterogenous data into the Warehouse: Data from different DBMSs (Data base management system), external information providers, various standard applications,... Tasks: Extraction (accessing different databases) Cleaning (resolving inconsistencies) Transformation (different formats, languages) Replication (importing a whole DB) Analyzing (detecting invalid values) Checking for data quality (correctness, completeness) Update metadata, if necessary
MIS: Pichai Takkabutr EAU 2005 10 Data Aggregation & Customization Getting (multidimensional) data out of the Warehouse as the input for: Reporting (summarized by: who, when, where, what) Query tools Online analytical processing (OLAP) Geographic information systems (GIS) Decision support systems (DSS) Executive information systems (EIS) Data Mining
MIS: Pichai Takkabutr EAU 2005 11 Implementation of a Data Warehouse Several providers (IBM, Oracle,...) offer Data Warehouse Systems. But: Warehouses are not sold as of-the-shelf products Available products often only support part of the functionality of a warehouse (middleware for information transport, database) Implementation of a valuable warehouse is a major project with major risk factors Data Warehouses need constant maintenance to stay usable
MIS: Pichai Takkabutr EAU 2005 12 Summary: Data Warehouse A data warehouse is a central repository for all or significant parts of the data that an enterprise's various business systems collect. It enables the management to access the available data in an efficient way, learn about trends make informed decisions.
MIS: Pichai Takkabutr EAU 2005 13 Summary Information technology constantly changes the relationship between customers and a company. Convenience and better service for customers are key factors for success. Intelligent gathering, integration and usage of information about the customer is vital in order to survive competition. Data Warehouses and Data Mining provide the components for mass customization.
MIS: Pichai Takkabutr EAU 2005 17 ADTs typically seen in textbooks and implemented in programming languages (or their libraries) include: String List Stack Queue Priority queue Complex number Associative array Multimap