Data Mining and Data Warehouse MCQs with answers Page - 5

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A

Admin • 828.03K Points
Coach

Q. Fact tables are ___________.

  • (A) completely demoralized.
  • (B) partially demoralized.
  • (C) completely normalized.
  • (D) partially normalized.

A

Admin • 828.03K Points
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Q. _______________ is the goal of data mining.

  • (A) to explain some observed event or condition.
  • (B) to confirm that data exists.
  • (C) to analyze data for expected relationships.
  • (D) to create a new data warehouse.

A

Admin • 828.03K Points
Coach

Q. Business Intelligence and data warehousing is used for ________.

  • (A) forecasting.
  • (B) data mining.
  • (C) analysis of large volumes of product sales data.
  • (D) all of the above.

A

Admin • 828.03K Points
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Q. The data administration subsystem helps you perform all of the following, except__________.

  • (A) backups and recovery.
  • (B) query optimization.
  • (C) security management.
  • (D) create, change, and delete information.

A

Admin • 828.03K Points
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Q. The most common source of change data in refreshing a data warehouse is _______.

  • (A) queryable change data.
  • (B) cooperative change data.
  • (C) logged change data.
  • (D) snapshot change data.

A

Admin • 828.03K Points
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Q. ________ are responsible for running queries and reports against data warehouse tables.

  • (A) hardware.
  • (B) software.
  • (C) end users.
  • (D) middle ware.

A

Admin • 828.03K Points
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Q. Query tool is meant for __________.

  • (A) data acquisition.
  • (B) information delivery.
  • (C) information exchange.
  • (D) communication.

A

Admin • 828.03K Points
Coach

Q. Classification rules are extracted from _____________.

  • (A) root node.
  • (B) decision tree.
  • (C) siblings.
  • (D) branches.

A

Admin • 828.03K Points
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Q. Dimensionality reduction reduces the data set size by removing ____________.

  • (A) relevant attributes.
  • (B) irrelevant attributes.
  • (C) derived attributes.
  • (D) composite attributes.

A

Admin • 828.03K Points
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Q. ___________ is a method of incremental conceptual clustering.

  • (A) corba.
  • (B) olap.
  • (C) cobweb.
  • (D) sting.

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