Data_Warehousing

Data Warehousing Determining which subjects will be created and populated in the data warehouse is called subject definition. A subject is a logical concept; for example, an organization’s customers, including their names, addresses, etc. From this business logic, a logical data model is developed. Next, the logical model is translated into a physical data model that defines the actual data storage architecture for the data warehouse. Physical models can be based on several design constructs, such as an entity relationship model, star schema, snowflake schema, persistent multidimensional store, or summary tables. Data transformations are used to convert and summarize operational data into a consistent, business-oriented format. Transformation of data consists of two distinct steps: 1) integration and conversion and 2) summarization. Integration and conversion resolves data inconsistencies in value definitions and formats among data. Summarization, consisting of both data, warehouse, model, physical, making, logical, business, view, tremendous, summarization, subject, schema, operational, integration, information, format, end, defines, customers, conversion, amounts, access, yield, without, warehousing, value, users, user, useful, two, translated, transformations, transformation, tools, technical, tables, summary, summarize, summarizations, subjects, store, storage, steps, star, sources, snowflake, several, rules, resources, resolves, reside