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Data warehouse Latest Interview Questions and Answers Part-5

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datawarehouse41. What does MetaData Respiratory contains?
Metadata respiratory contains Definition of data warehouse, Business Metadata, Operational Metadata, Data for mapping from operational environment to data warehouse and the Alorithms for summarization

42. How does a Data Cube help?
Data cube help us to represent the data in multiple dimensions. The data cube is defined by dimensions and facts.

43. Define Dimension?
The dimensions are the entities with respect to which an enterprise keep the records.

44. Explain Data mart?
Data mart contains the subset of organisation-wide data. This subset of data is valuable to specific group of an organisation. in other words we can say that data mart contains only that data which is specific to a particular group.

45. What is Virtual Warehouse?
The view over a operational data warehouse is known as virtual warehouse.

46. List the phases involved in Data warehouse delivery Process?

The stages are IT strategy, Education, Business Case Analysis, technical Blueprint, Build the version, History Load, Ad hoc query,Requirement Evolution, Automation, Extending Scope.

47. Explain Load Manager?
This Component performs the operations required to extract and load process. The size and complexity of load manager varies between specific solutions from data warehouse to data warehouse.

48. Define the function of Load Manager?
Extract the data from source system.Fast Load the extracted data into temporary data store.Perform simple transformations into structure similar to the one in the data warehouse.

49. Explain Warehouse Manager?
Warehouse manager is responsible for the warehouse management process.The warehouse manager consist of third party system software, C programs and shell scripts.The size and complexity of warehouse manager varies between specific solutions.

50. Define functions of Warehouse Manager?
The Warehouse Manager performs consistency and referential integrity checks, Creates the indexes, business views, partition views against the base data, transforms and merge the source data into the temporary store into the published data warehouse, Backup the data in the data warehouse and archives the data that has reached the end of its captured life.

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