Question 1

When building a K-means clustering model, you notice that the clusters did not segment on variables

that you expected. What should you do?

Options :

A : Decrease the value of K

B : Multiply each variable by its standard deviation

C : Add the WSS to each variable

D : Check that the data was properly scaled

Answer: D

Question 2

What is a key consideration when preparing a presentation intended for analysts?

Options :

A : Describe how to implement the model

B : Provide talking points to promote or evangelize the project

C : Emphasize the business benefits of implementing the model

D : Focus on clean simple-to-understand visuals

Answer: D

Question 3

What is a benefit of Spark in-memory data processing as opposed to using MapReduce?

Options :

A : Avoids writing intermediate data to disk, which speeds up processing

B : Supports processing unstructured data, which MapReduce does not allow

C : Removes the need to use disks at all, which reduces cost

D : Allows parallel processing, which MapReduce does not support

Answer: A

Question 4

What converts SQL-like commands into either Tez, Spark, or MapReduce jobs that are submitted to

the Hadoop cluster?

Options :

A : Pig

B : HBase

C : Hive

D : Mahout

Answer: C

Question 5

What is a recommended use case for regular expressions?

Options :

A : Linear regression

B : Decision trees

C : Logistic regression

D : In-database text analysis

Answer: D