Page 60 - Demo

%u062c%u0645%u064a%u0639 %u0627%u0644%u062d%u0642%u0648%u0642 %u0645%u062d%u0641%u0648%u0638%u0629 %u0640 %u0627%u0625%u0644%u0639%u062a%u062f%u0627%u0621 %u0639%u0649%u0644 %u062d%u0642 %u0627%u0645%u0644%u0624%u0644%u0641 %u0628%u0627%u0644%u0646%u0633%u062e %u0623%u0648 %u0627%u0644%u0637%u0628%u0627%u0639%u0629 %u064a%u0639%u0631%u0636 %u0641%u0627%u0639%u0644%u0647 %u0644%u0644%u0645%u0633%u0627%u0626%u0644%u0629 %u0627%u0644%u0642%u0627%u0646%u0648%u0646%u064a%u062960possible summary views may be materialized. A virtual warehouse is easy to build but requires excess capacity on operational database servers. Extraction, Transformation, and Loading (ETL): 1-Data extraction: which typically gathers data from multiple, heterogeneous, and external sources. 2-Data cleaning: which detects errors in the data and rectifies them when possible. 3-Data transformation: which converts data from legacy or host format to warehouse format. 4-Load: which sorts, summarizes, consolidates, computes views, checks integrity, and builds indices and partitions. 5-Refresh: which propagates the updates from the data sources to the warehouse. Metadata Repository: %u25fc Metadata are data about data. When used in a data warehouse, metadata are the data that define warehouse objects. It stores: a-Description of the structure of the data warehouse (schema, view, dimensions, hierarchies, data mart locations and contents b-Operational meta-data: data lineage (history of migrated data and transformation path), currency of data (active, archived, or purged), monitoring information (warehouse usage statistics, error reports, audit trails) c-The algorithms used for summarization d-The mapping from operational environment to the data warehouse eData related to system performance: warehouse schema, view and derived data definitions f-Business data: business terms and definitions, ownership of data, charging policies II. Data Warehouse Modeling: Data Cube and OLAP A data warehouse is based on a multidimensional data model which views data in the form of a data cube, A data cube allows data to be modeled and viewed in multiple dimensions. It is defined by dimensions and facts. In general terms, dimensions are the perspectives or entities with respect to which an organization wants to keep records.