Latest Answer: RalfKimball: he follows bottum-up approach i.e., first create individual Data Marts from the existing sources and then create Data Warehouse.BillImmon: he follows top-down approach i.e., first create Data Warehouse from the existing ...
Latest Answer: Junk Dimension also called as garbage dimension. A garbage dimension is a dimension that consists of low-cardinality columns such as codes, indicators, status,and flags. The garbage dimension is also referred to as a junk dimension. Attributes in a garbage ...
What is the definition of normalized and denormalized view and what are the differences between them
Latest Answer: The Fact table is central table in Star schema, Fact table is kept Normalized because its very bigger and so we should avoid redundant data in it. Thats why we make different dimensions there by making normalized star schema model which helps in query ...
Latest Answer: E-R Modeling is a model for OLTP, optimized for Operational database, namely insert, update, delete data and stressing on data relational integrity.Dimensional Modeling is a model for OLAP, optimized for retrieving data because it's uncommon to update ...
Latest Answer: A fact,which can be used across multiple datamarts is called as conformed fact. ...
Latest Answer: There are four methods in which one can build a datawarehouse.1. Top-Down (Emphasizes the DW. )2. Bottom-Up (Emphasizes data marts.)3. Hybrid (Emphasizes DW and data marts; blends “top-down” and “bottom-up” methods.)4. Federated (Emphasizes the need to ...
Latest Answer: Bus Schema : Let we consider/explain these in x,y axis Dimension Table : A,B,C,D,E,F ...
Information Packages(IP) are advanced by some author as a way of building dimensional models - e.g. star schemas. Explain what IPs are and Give an example of it\'s use in building a dimensional model.
Latest Answer: No Tool testing in done in DWH, only manual testing is done. ...
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