DBMS-Data Warehousing and Data Mining Questions and Answers

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Data Warehousing and Data Mining questions with answers are crucial for understanding how organizations manage and analyze large datasets. These DBMS programming questions and answers explore concepts like ETL processes, OLAP operations, clustering, classification, and association rule mining. Practicing these questions helps students gain clarity on real-world data analytics and storage architecture, often tested in company placement papers and technical interviews. If you’re preparing for TCS, Capgemini, or Wipro, reviewing these DBMS-based data mining questions will strengthen your database and analytics knowledge for exams and interviews

DBMS-Data Warehousing and Data Mining

Showing 10 of 36 questions

11. OLAP is a database interface tool that allows users to quickly navigate within their data.

  • TRUE
  • FALSE
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12. Data mining is the process of extracting valid, previously unknown, cmprehensible and actionable information from large database and using it to make crucial business decisions

  • TRUE
  • FALSE
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13. The goal off data miningg is to create models for decision-making that predict future behaviouur based on  analyses of past activity.

  • TRUE
  • FALSE
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14. Data mining predicts the future behaviour of certain attributes within data.

  • TRUE
  • FALSE
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15. In the association rules in data mining, the database is regarded as a collection of transactions, each involving a set of item.

  • TRUE
  • FALSE
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16. In data mining, classifiction is the process of learning a model that describes different classes of data.

  • TRUE
  • FALSE
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17.  Which of the following is a characterstic of the data in a data warehouse ?

  • Non-volatile.
  • Subject-oriented
  • Time-variented.
  • All of these
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18. Data warehouse is a special type of database with a

  • Single archive of data
  • Consistent archieve of data
  • Complete archive of data
  • All of these
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19. Data warehouses, extract information for strategic use of the organisation in reducing  costs and improving revenues, out ot

  • Legacy systems
  • secondary storage.
  • main memory
  • None of these
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20. The advancements in technology and the develpment of microcomputers (PCs) along with data-orientation in form of relational databases, drove the emergence of end-user computing during

  • 1970s and 1980s
  • 1980s and 1990s
  • 1990s and 2000s
  • the start of the 21st century.
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