DASCA Senior Data Scientist - SDS Exam Questions [2026]

QUESTION NO: 1
What is Scrum?

A. Scrum is a subset of Agile B. Agile is a subset of Scrum C. Scrum and Agile are the same D. None of the above

Correct Answer: A

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QUESTION NO: 2
Which of the following standardizes scores similar to a percentile rank but preserves equal interval properties of a Z-score?

A. Medium Curve Equivalent (MCE) B. High Curve Equivalent (HCE) C. Normal Curve Equivalent (NCE) D. Trend analysis E. None of the above

Correct Answer: C

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QUESTION NO: 3
Semi-structured data does NOT include:

A. File systems B. Schema-full data C. Scientific data D. Database system

Correct Answer: B

QUESTION NO: 4
Which of the following is NOT a cluster management tool?

A. Apache Hadoop B. Apache Ambari C. Zettaset Orchestrator D. Apache Mesos

Correct Answer: A

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QUESTION NO: 5
The main purpose of a Statement Of Work (SOW) is to get:

A. What the priorities are B. All of the above C. Everybody on the same page about what work should be done D. What expectations are realistic E. None of the above

Correct Answer: B

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QUESTION NO: 6
In regression, the principle of machine learning is used to optimize the parameters to:

A. Calculate the closest possible outcomes B. None of the above C. Both A and B D. Minimize the approximation error

Correct Answer: C

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QUESTION NO: 7
Which of the following is NOT a valid section of Big Data Strategy document?

A. Business strategy B. Key business initiatives C. Key business entities D. Business decisions E. Key decisions

Correct Answer: D

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QUESTION NO: 8
Which of these statements reflects a null hypothesis?

A. Men will score higher than women on spatial awareness B. As temperature increases, so too will the level of aggression C. There will be no relationship between caffeine consumption and performance D. There will be a significant difference between group 1 and group 2 E. Women will score higher than men on empathy

Correct Answer: C

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QUESTION NO: 9
Which of the following is True about Time Series Analysis?

A. Predicting when/whether an event will occur, such as a failure of the machine generating the data B. Projecting the value of the time series at future points in time, such as a stock whose price we want to predict C. All of the above D. Identifying interesting patterns in a corpus of time series data that is too large for a human to comb through E. Both A and B

Correct Answer: C

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