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DASCA Senior Data Scientist Sample Questions (Q11-Q16):

NEW QUESTION # 11
The Big Data Vision Workshop process is ideal for organizations who:

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

Answer: D

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 # 12
Which of the following is a DevOps Practice?

A. All of the above
B. Continuous build
C. Continuous integration
D. Continuous delivery

Answer: A

Explanation:
DevOps is a collaborative practice that integrates software development (Dev) and IT operations (Ops) to shorten development cycles and deliver applications reliably. Common DevOps practices include:
Continuous Build (Option A): Automating compilation and packaging of source code to ensure consistent builds.
Continuous Integration (Option B): Developers frequently merge code into a shared repository, which is automatically tested to catch integration issues early.
Continuous Delivery (Option C): Automating software release pipelines so applications can be deployed to production quickly and reliably.
Since all of these are essential DevOps practices, the correct answer is Option D (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Business Applications of Data Science: DevOps Practices in Data Science Projects.

NEW QUESTION # 13
Semi-structured data does NOT include:

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

Answer: D

Explanation:
Semi-structured data falls between structured data (e.g., relational databases with fixed schema) and unstructured data (e.g., free text, audio, video). It typically includes irregular or flexible schema information, such as XML, JSON, email data, or log files.
Option A (Database systems): Correct, databases may hold semi-structured content (e.g., JSON or XML columns).
Option B (File systems): Correct, file-based storage (logs, JSON, Avro, CSV) often contains semi-structured data.
Option C (Scientific data): Correct, many scientific applications generate semi-structured data formats (sensor readings, genomic sequences, etc.).
Option D (Schema-full data): Correct Answer. Schema-full (strict schema-defined relational tables) represent structured data, not semi-structured.
Thus, semi-structured data does NOT include schema-full data.
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Big Data Fundamentals: Data Types & Sources.

NEW QUESTION # 14
Maximum Likelihood Estimation (MLE) is a way to frame:

A. Small class of problems in Data Science
B. Both A and C
C. Large class of problems in HDFS
D. Large class of problems in Data Science
E. Small class of problems in HDFS

Answer: D

Explanation:
Maximum Likelihood Estimation (MLE) is a statistical method used to estimate the parameters of a model by maximizing the likelihood function - i.e., finding the parameters that make the observed data most probable.
Option A: Correct. MLE provides a framework for a large class of problems in data science, including regression, classification, generative models, and probabilistic inference.
Option B: Incorrect - it applies to many problems, not just a small subset.
Option C & D: Incorrect. HDFS (Hadoop Distributed File System) is a storage technology, unrelated to MLE.
Option E: Incorrect because C is invalid.
Thus, the correct answer is Option A (Large class of problems in Data Science).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Statistical Foundations: Maximum Likelihood Estimation and Inference in Data Science.

NEW QUESTION # 15
Which of the following can visualize variations in the base data, which can be used to identify outliers in the data for further investigation?

A. None of the above
B. Scatter Plot
C. Box Plots
D. Trend Analysis
E. Histogram

Answer: C

Explanation:
Box plots (or Whisker plots) are statistical graphics that represent data distribution through:
Minimum, First Quartile (Q1), Median, Third Quartile (Q3), and Maximum.
Outliers are plotted as individual points beyond the whiskers.
This makes them particularly powerful for:
Identifying outliers in data.
Comparing distributions across categories.
Understanding variability in data.
Option A (Trend Analysis): Shows temporal patterns, not individual outliers.
Option C (Histogram): Shows frequency distribution but does not explicitly highlight outliers.
Option D (Scatter Plot): Shows relationships between variables but doesn't focus on statistical outliers in one distribution.
Thus, the correct answer is Option B (Box Plots).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Data Visualization Tools: Box Plots for Outlier Detection.

NEW QUESTION # 16
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Exam DASCA SDS Cram Questions, Reliable SDS Test Pattern

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DASCA Senior Data Scientist Sample Questions (Q11-Q16):

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