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Chapter 1: Data Warehousing

Chapter 1: Data Warehousing presents about Basic Concepts of data warehousing; Data warehouse architectures, Some characteristics of data warehouse data, The reconciled data layer, Data transformation, The derived data layer, The user interface. | HCMC UT, 2008 Chapter 1: Data Warehousing 1.Basic Concepts of data warehousing 2.Data warehouse architectures 3.Some characteristics of data warehouse data 4.The reconciled data layer 5.Data transformation 6.The derived data layer 7. The user interface Motivation “Modern organization is drowning in data but starving for information”. Operational processing (transaction processing) captures, stores and manipulates data to support daily operations. Information processing is the analysis of data or other forms of information to support decision making. Data warehouse can consolidate and integrate information from many internal and external sources and arrange it in a meaningful format for making business decisions. Definition Data Warehouse: (W.H. Immon) A subject-oriented, integrated, time-variant, non-updatable collection of data used in support of management decision-making processes Subject-oriented: e.g. customers, patients, students, products Integrated: Consistent . | HCMC UT, 2008 Chapter 1: Data Warehousing 1.Basic Concepts of data warehousing 2.Data warehouse architectures 3.Some characteristics of data warehouse data 4.The reconciled data layer 5.Data transformation 6.The derived data layer 7. The user interface Motivation “Modern organization is drowning in data but starving for information”. Operational processing (transaction processing) captures, stores and manipulates data to support daily operations. Information processing is the analysis of data or other forms of information to support decision making. Data warehouse can consolidate and integrate information from many internal and external sources and arrange it in a meaningful format for making business decisions. Definition Data Warehouse: (W.H. Immon) A subject-oriented, integrated, time-variant, non-updatable collection of data used in support of management decision-making processes Subject-oriented: e.g. customers, patients, students, products Integrated: Consistent naming conventions, formats, encoding structures; from multiple data sources Time-variant: Can study trends and changes Nonupdatable: Read-only, periodically refreshed Data Warehousing: The process of constructing and using a data warehouse Data Warehouse—Subject-Oriented Organized around major subjects, such as customer, product, sales. Focusing on the modeling and analysis of data for decision makers, not on daily operations or transaction processing. Provide a simple and concise view around particular subject issues by excluding data that are not useful in the decision support process. Data Warehouse - Integrated Constructed by integrating multiple, heterogeneous data sources relational databases, flat files, on-line transaction records Data cleaning and data integration techniques are applied. Ensure consistency in naming conventions, encoding structures, attribute measures, etc. among different data sources E.g., Hotel price: currency, tax, breakfast covered, etc. When data is