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DASCA Senior Data Scientist Sample Questions (Q19-Q24):

NEW QUESTION # 19
Which of the following is TRUE for "By" analysis?

A. All of the above
B. The "By" analysis technique reinforces the process of "thinking like a data scientist."
C. Both B and C
D. "By" analysis is a technique by which business subject matter experts (SMEs) and the Data Science team could collaborate to uncover new variables and metrics that might be better predictors of business performance.
E. "By" analysis is used to create a collaborative technique to drive alignment between the business users and the data scientists to identify and brainstorm variables and metrics that might be better predictors of business performance.

Answer: A

Explanation:
"By" analysis is one of the foundational approaches recommended in the DASCA Data Scientist Knowledge Framework for structuring problem-solving in data science. The purpose of "By" analysis is to enable data scientists and business stakeholders to think beyond obvious data correlations and uncover deeper drivers of business outcomes.
At its core, the technique reinforces the discipline ofthinking like a data scientist(Option A). This involves reframing business questions into analytical structures and asking "What drives this metricbywhich factors?" For example, customer churn might be analyzedbydemographics, purchase behavior, or service usage. This structured mindset is critical for ensuring scientific rigor in business problem analysis.
In addition, "By" analysis emphasizes collaboration betweenSubject Matter Experts (SMEs)andData Science teams(Option B). SMEs bring contextual domain knowledge, while data scientists bring analytical and statistical expertise. Together, they brainstorm possible explanatory variables or metrics that could become strong predictors of business performance.
Furthermore, the process provides acollaborative bridgebetween business and technical stakeholders (Option C). It ensures that the exploration of data is not isolated in silos but is grounded in both domain insights and advanced analytical methods. This alignment is crucial for building models that are not only technically sound but also relevant and actionable in real-world business contexts.
Since Options A, B, and C are correct and complementary, the best choice isOption E: All of the above.
Reference:DASCA Data Scientist Knowledge Framework (DSKF) -Data Science Process Fundamentals & Collaborative Analysis Techniques(Official DASCA Study & Exam Preparation Guide).

NEW QUESTION # 20
The Big Data Vision Workshop process is ideal for organizations who:

A. All of the above
B. Both A and B
C. Have a desire to leverage the Big Data Vision Workshop to identify where and how to leverage data and analytics to power their business models
D. Have a wealth of data that they do not know how to monetize
E. Have a desire to leverage Big Data to transform their business but do not know where and how to start

Answer: A

Explanation:
The Big Data Vision Workshop is an early-phase framework designed to help organizations shape their data- driven transformation journey. It is particularly beneficial when:
Option A: Organizations want to leverage big data but lack clarity on where to start.
Option B: Organizations already have large volumes of data but struggle to derive monetization strategies from it.
Option C: Organizations want to identify use cases where data and analytics can enhance or even redefine their business models.
Since all three statements apply, the correct answer is Option E (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Business Applications of Data Science: Big Data Vision Workshop.

NEW QUESTION # 21
Which of the following is a useful feature of functional programming?

A. Higher-Order Functions (HOFs)
B. Lazy Evaluation
C. All of the above
D. Immutable Data

Answer: C

Explanation:
Functional programming (FP) is a paradigm widely adopted in data science and big data tools (e.g., Spark with Scala/Python). Its useful features include:
Option A (Higher-Order Functions): Functions can take other functions as arguments or return them, enabling powerful abstractions like map(), reduce(), and filter().
Option B (Immutable Data): Ensures reliability and thread-safety, crucial for distributed computing. Once created, data structures cannot be modified, preventing side effects.
Option C (Lazy Evaluation): Computations are delayed until results are needed, improving performance in large-scale data operations.
Since FP leverages all three features, the correct answer is Option D (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming for Data Science: Functional Programming in Data Science Tools.

NEW QUESTION # 22
Which of the following is used to summarize a dataset by showing the median, quantiles, and min/max values for each of the variables?

A. Box Plots
B. Bar Charts
C. Histogram
D. Scatter Chart
E. Pie Charts

Answer: A

Explanation:
A Box Plot (also called Whisker Plot) is a visualization tool used to summarize data distribution using five- number summary:
Minimum,
First quartile (Q1),
Median (Q2),
Third quartile (Q3),
Maximum.
It also highlights outliers explicitly.
Option A (Box Plots): Correct.
Option B (Pie Charts): Show proportions, not distribution.
Option C (Histogram): Shows frequency distribution but not quartiles/median.
Option D (Scatter Chart): Used for relationships between two variables, not summary statistics.
Option E (Bar Charts): Compare categories, not statistical spread.
Thus, the correct answer is Option A (Box Plots).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Data Visualization Tools: Box Plots and Statistical Summaries.

NEW QUESTION # 23
What is the agenda of discussion at a "stand up" meeting of an Agile team?

A. All of the above
B. What they are planning to do today
C. Both A and B
D. Any roadblocks they are running into
E. What they accomplished the previous day

Answer: A

Explanation:
A daily stand-up meeting (also called a daily Scrum) is a short meeting (usually 15 minutes) that Agile teams hold to synchronize progress. Its agenda is structured around three key questions:
What was accomplished yesterday? (Progress review).
What is planned for today? (Work alignment).
What impediments or roadblocks exist? (Barriers identification).
This process enhances transparency, communication, and accountability, ensuring the team can quickly address obstacles and stay aligned with sprint goals.
Option A: Correct - yesterday's work is discussed.
Option B: Correct - today's planned tasks are outlined.
Option C: Correct - roadblocks are highlighted.
Option D: Incomplete since it misses C.
Option E: Correct - covers all agenda items.
Thus, the correct answer is Option E (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Agile Practices in Data Science Projects.

NEW QUESTION # 24
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