Data Warehouse Management MCQ

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Question 1 : A data warehouse can be used to analyze a particular ________

  1. graph
  2. chart
  3. domain
  4. subject
  

Question 2 : which information is not provided by Information packages

  1. Define the common subject areas
  2. date of full refresh
  3. Establish data granularity
  4. Estimate data warehouse size
  

Question 3 : Periodic Status is

  1. data in which changes to existing records cause the previous version of the records to be eliminated
  2. the value of the attribute is preserved as the status every time a change occurs
  3. data that are never altered or deleted once they have been added
  4. the value of the attribute at this moment of time.
  

Question 4 : Comparison of the general features of the target class data object against the general features of objects from one or multiple contrasting classes is a process of

  1. Data Characterization
  2. Data Classification
  3. Data discrimination
  4. Data selection
  

Question 5 : After the initial load, the data warehouse is kept up-to-date by two actions: REFRESH and UPDATE. As the number of records increase in a Data Warehouse, cost of update operation ______________ .

  1. decreases
  2. increases
  3. remains constant
  4. is same as cost of Refresh
  

Question 6 : The values of an ________ attribute provide enough information to order objects.

  1. ratio
  2. Binary
  3. Interval
  4. ordinal
  

Question 7 : As per the concept of KDD process, which of the following statement is valid ?

  1. KDD and Data Mining have no connection at all
  2. KDD is one of the steps in Data Mining
  3. Data Mining is one of the steps in KDD process
  4. KDD and Data Mining mean the same
  

Question 8 : information stored in the data warehouse.

  1. additive atleast over one dimension
  2. Only numeric measures are used
  3. All possible summaries are used
  4. It is additive over every dimension of its dimensionality
  

Question 9 : Converting data from different sources into a common format for processing is called as ________.

  1. Selection
  2. Preprocessing
  3. Transformation
  4. Interpretation
  

Question 10 : Binary attribute are

  1. This takes only two values. In general, these values will be 0 and 1 and .they can be coded as one bit
  2. This takes only three values.
  3. This takes only four values.
  4. It cant take any value.
  

Question 11 : It is measured on a scale of equal size units,these attributes allows us to compare such as temperature in C or F and thus values of attributes have order.

  1. Interval Scaled attribute
  2. Ratio scaled attribute
  3. Binary attribute
  4. Ternary attribute
  

Question 12 : Which of the following is not a valid Visualization technique ?

  1. Scatter plot
  2. Decision Tree
  3. Box plot
  4. Histogram
  

Question 13 : The _______numerical measure which tells that two objects are alike

  1. dissimilarity
  2. clarity
  3. non clarity
  4. simmilarity
  

Question 14 : Removing duplicate records is a data mining process called ____________ .

  1. Data isolation
  2. Recovery
  3. Data Cleaning
  4. Data dredging
  

Question 15 : _______________ is a process of taking operational data from one or more sources and mapping it, field by field, onto a new data structure in the data warehouse

  1. Transformation
  2. Cleansing
  3. Integration
  4. Scrubbing
  

Question 16 : __________ may be defined as the data objects that do not comply with the general behavior or model of the data available.

  1. Evolution Analysis
  2. Prediction
  3. Classification
  4. Outlier Analysis
  

Question 17 : How many coefficients do you need to estimate in a simple linear regression model (One independent and one dependent variable)?

  1. 1
  2. 2
  3. 3
  4. 4
  

Question 18 : The mapping or classification of a class with some predefined group or class is known as?

  1. Data Characterization
  2. Data Discrimination
  3. Data Subset
  4. Data set
  

Question 19 : To extract rules in supervised learning __________is used

  1. root node
  2. sibling
  3. decision trees
  4. branches
  

Question 20 : from the given options______ is a predictive model

  1. Clustering
  2. Regression
  3. Summarization
  4. Association rules
  

Question 21 : Euclidean distance measure is

  1. A stage of the KDD process in which new data is added to the existing selection.
  2. The process of finding a solution for a problem simply by enumerating all possible solutions according to some pre-defined order and then testing them
  3. The distance between two points as calculated using the Pythagoras theorem
  4. The distance between two points as calculated using interval scale
  

Question 22 : Given two objects represented by the tuples (22, 1, 42, 10) and (20, 0, 36, 8):Compute the Euclidean distance between the two objects.

  1. 6.32
  2. 6.71
  3. 6.15
  4. 6.22
  

Question 23 : The following rule is an example of which association rule.{ age (X, “20…...29”) ^ occupation(X, “student”)→ buys(X, “laptop”) }.

  1. multilevel association rules
  2. interlevel association rules
  3. multidimensional association rules
  4. intralevel association rules
  

Question 24 : Repeating the holdout many times is called ______

  1. random subsampling
  2. cross validation
  3. bootstrap
  4. bagging
  

Question 25 : Which algorithm requires fewer scans of data?

  1. Apriori
  2. FP growth
  3. Apriori and FP Growth
  4. decision
  
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