![]() ![]() ![]() Time-variance: Timeliness of data and access terms 8. Non-volatility: Stable data storage medium 4. Integration: Consistency of defining parameters 3. Subject Orientation: Data organized by subject 2. (Nov/Dec 2009) There are four key characteristics which separate the data warehouse from other major operational systems: 1. List the characteristics of a data ware house. The slice operation performs a selection on one dimension of the cube resulting in a sub cube.The dice operation defines a sub cube by performing a selection on two (or) more dimensions. Such a table is easy to maintain and saves storage space. (Nov/Dec 2008) The dimension table of the snowflake schema model may be kept in normalized form to reduce redundancies. Explain the differences between star and snowflake schema. Additional metadata are created and captured for time stamping any extracted data, the source of the extracted data, and missing fields that have been added by data cleaning or integration processes. ![]() Metadata are created for the data names and definitions of the given warehouse. When used in a data warehouse, metadata are the data that define warehouse objects. What is data warehouse metadata? (Apr/May 2008) Metadata are data about data. These systems are known as on-line analytical processing systems. Such systems can organize and present data in various formats. (Apr/May 2008), (May/June 2010) If an on-line operational database systems is used for efficient retrieval, efficient storage and management of large amounts of data, then the system is said to be on-line transaction processing.Data warehouse systems serves users (or) knowledge workers in the role of data analysis and decision-making. Many complex data mining queries can be answered by multifeature cubes without any significant increase in computational cost, in comparison to cube computation for simple queries with standard data cubes. What are the uses of multifeature cubes? (Nov/Dec 2007) multifeature cubes, which compute complex queries involving multiple dependent aggregates at multiple granularity. ![]()
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