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Chapter 11 Question 3 a. Transient data can be overwritten with new values when updated, while periodic data is intended to remain in the database and either be supplemented with the new data or stored for posterity along newer entities created for newer data. b. A data warehouse is a non-updatable collection of data used for supporting management decisionmaking processes. A data mart is similar but more limited in scope, and focused at a particular user group for more specific purposes. An operational data store is updated frequently and used by operational users for decision support.. c. Reconciled data is meant to be the single authoritative source for decision support applications while derived data is selected and formatted to be used only by user-oriented decision support. d. Fact tables hold data that can be represented as facts, like numbers and quantities, while dimension tables hold contextual information and descriptive data about subjects. e. A star schema is a dimensional data model where dimensional data is separated out from factual data. A snowflake schema is an extension of the star schema in which the database’s dimensional data tables are normalized into multiple related tables. f. The independent data mart is full of data from the operational environment without use of a data warehouse, and a dependent data mart is the opposite, only filled with data from the data warehouse. A logical data mart is created from a relational view of the data warehouse and is not a separate database but a tool for gaining new perspective on the existing data. Question 4 The five trends among organizations that are necessitating data warehousing are large and varied organizations needing multiple databases that all use the same data, the practical impossibility of synchronizing multiple databases without centralized data, the advantage of analyzing the data and activities of the organization in a balanced and generalized way, the advantage of improving customer relationships through analysis of the data related to the customer, and the advantage of also improving supplier relationships through use of data analysis. Question 14 A logical data mart can be a useful tool for analysis of the data in a data warehouse, and since it isn’t created as a separate database but rather by creating a different relational view of the existing database, it is made in the same space as the warehouse and will not need any additional storage space, technology, or loading routines. A logical data mart will always be up to date as the data in the view is created only on the instantiation of the view. Unfortunately all of this reuse of the existing data in the current space rather than copying the values to a new data mart means that the operations can require much more time or computing resources to run while the data is processed, so the technique should be limited to use with small- to medium-sized databases, or in faster and more powerful computing environments. Question 17 Data warehouses and data marts almost always include time as a dimension since they usually record facts about other dimensions over time. Time and date become critical relations among the entire rest of the data store, useful for analyses of all other data in relation to certain other events and conditions, in both the organization and its environment.