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Data Mining and Business Intelligence Practice Test
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Avg score: 50% • Most missed: “The data Warehouse is __________.”

How Data Mining helps with Business Intelligence:
Data mining is an essentail component of business intelligence (BI). Once all the valuable information has been extracted from the data, businesses turn it into actionable knowledge - in other words, business intelligence.

Types of Data mining include: Clustering. Prediction. Classification. Genetic Algorithms. Regression. Association rule learning. Anomaly detection. Artificial Neural Network Classification.

Data Mining and Business Intelligence Practice Test
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25 Questions

1. Employs the supervised mode of learning.
2. Removing duplicate records is a process called____________.
3. RBF hidden layer units have a receptive field which has a________; that is, a particular input value at which they have a maximal output.
4. GA stands for ____ .
5. _________helps to integrate, maintain and view the contents of the data warehousing system.
6. ROI is an acronym of _______.
7. The__________engine for a data warehouse supports query-triggered usage of data.
8. Which of the following is not a old detail storage medium?
9. Prediction can be viewed as forecasting a value
10. The full form of KDD is__________.
11. The a priori frequent itemset discovery algorithm moves in the lattice
12. Pick out a hierarchical clustering algorithm
13. Various visualization techniques are used in_________step of KDD.
14. 7 If T consist of 500000 transactions, 20000 transaction contain bread, 30000 transaction contain jam, 10000 transaction contain both bread and jam. Then the confidence of buying bread with jam is____________.
15. The absolute number of transactions supporting X in T is called _______.
16. Incorrect or invalid data is known as _______.
17. _____________is an important functional component of the metadata.
18. The granularity of the fact is the ___________ of detail at which it is recorded.
19. The partition algorithm uses scans of the databases to discover all frequent sets
20. _____ is used to proceed from very specific knowledge to more general information.
21. The ______of data could result in the disclosure of information that is deemed to be confidential.
22. In _____ , the value of an attribute is examined as it varies over time.
23. ____________is data collected from natural systems.
24. Which of the following is a data set in the popular UCI machine-learning repository?
25. A directory to help the DSS analyst locate the contents of the data warehouse isseen in __________.

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