Data Warehousing Test

Data Warehousing Test


The main objects used by OLAP programs are:

a. Multidimensional cubes
b. Metadata
c. RDBMS tables
d. Fact tables
e. Pivot tables

Which of the following type of data is most likely to be stored on some form of mass storage ?

a. Metadata
b. Highly summarised data
c. Lightly summarised data
d. Current detail data
e. Older detail data

A multidimensional cube records a set of data derived from:

a. Fact tables
b. Pivot tables
c. Dimensions
d. Fact tables and Dimensions
e. Fact tables and Pivot tables

Which technique of Data Mining involves developing mathematical structures with the ability to learn?

a. Clustering and Segmentation
b. Neural Networks
c. Fuzzy Logic
d. Linear Regression Analysis
e. Rule based Analysis

The applications of Data Mining would not include:

a. Discovering buying-patterns for cross selling
b. Financial market prediction
c. Discovering errors made during data entry
d. Discovering which customer is most profitable
e. Credit assessment

The movement of data from one environment to another is known as:

a. Data Migration
b. Normalization
c. Replication
d. Data Mining
e. Data Cleansing

Data Mining is also known as

a. Data Extraction
b. Data Cleansing
c. Data Archiving
d. Knowledge Discovery in Databases (KDD)
e. Data Preservation

Which Data Mining technique partitions the database so that each partition or group is similar according to some criteria or metric ?

a. Clustering and Segmentation
b. Induction
c. Neural Networks
d. Data Visualisation
e. Linear Regression Analysis

In the Discovery model of Data Mining, the emphasis is on which of the following?

a. The system automatically discovering important information hidden in the data
b. The user who is responsible for formulating the hypothesis and issuing the query on the data to affirm or negate the hypothesis
c. Volume of the data being examined
d. Timeliness of the data
e. Speed with which the data is examined

Which of the following rules would be considered the central core of OLAP?

a. Multidimensional Conceptual View
b. Intuitive Data Manipulation
c. Accessibility
d. Batch Extraction vs Interpretative
e. Transparency

Prev1 of 6

Share This Post