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DASCA Senior Data Scientist Sample Questions (Q24-Q29):

NEW QUESTION # 24
Bernoulli random variable is a type of:

A. Continuous random variable
B. Both A and B
C. Sometimes Discrete or sometimes Continuous random variable
D. Discrete random variable

Answer: D

Explanation:
A Bernoulli random variable is the simplest form of discrete random variable.
It can take only two values:
1 with probability p (success).
0 with probability (1 - p) (failure).
Since the outcomes are finite (binary), it is a discrete random variable.
Option B (Continuous): Incorrect, as continuous variables take values from an interval (e.g., real numbers).
Option C and D: Incorrect, as Bernoulli is always discrete, never continuous.
Thus, the correct answer is Option A (Discrete random variable).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Probability & Statistics for Data Science: Random Variables and Bernoulli Distribution.

NEW QUESTION # 25
Which of the following is correct?
i. LaTeX is used to publish work in a scientific journal
ii. LaTeX is a markup language that can be compiled into formatted documents iii. LaTeX is for publishing scientific papers

A. i, iii
B. i, ii, iii
C. ii, iii
D. i, ii

Answer: B

Explanation:
LaTeX is a high-quality typesetting system widely used in academia, particularly in scientific publishing.
Statement i: Correct. LaTeX is widely used to prepare manuscripts for scientific journals, theses, and technical reports.
Statement ii: Correct. LaTeX is a markup language (similar to HTML in concept) that compiles into formatted PDFs/documents.
Statement iii: Correct. LaTeX is a standard for publishing scientific papers due to its ability to handle complex mathematical equations, references, and formatting.
Thus, all three statements are true # Option B (i, ii, iii).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming Tools for Data Science: LaTeX for Scientific Documentation.

NEW QUESTION # 26
Which of the following is TRUE for data lake?

A. The data lake enables organizations to gather, manage, enrich, and analyze many new sources of data, whether structured or unstructured
B. The data lake enables organizations to treat data as an organizational asset to be gathered and nurtured versus a cost to be minimized
C. The data lake can make both of the Business Intelligence and Data Science environments less agile and more productive
D. The data lake can make both of the Business Intelligence and Data Science environments more agile and more productive
E. None of the above

Answer: A,B,D

Explanation:
But per MCQ single-choice format # answer: A (though ideally A, B, C are correct).
A data lake is a centralized repository designed to store raw, structured, semi-structured, and unstructured data at scale. It provides:
Agility and productivity (Option A): Data lakes support flexible ingestion and faster access, making BI and data science environments more efficient.
Data integration (Option B): They handle multiple types of data, enabling advanced analytics and machine learning use cases.
Data as an asset (Option C): They shift perspective, treating data as a strategic resource, not just a storage cost.
Option D: Incorrect. Data lakes improve agility, not reduce it.
Option E: Incorrect, since multiple true statements exist.
Thus, the correct choice per DASCA context is Option A (with B and C also being true).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Data Engineering: Data Lakes vs Warehouses.

NEW QUESTION # 27
Which of the following is TRUE for Business Metamorphosis?

A. Both A and C
B. The Business Metamorphosis phase is where organizations integrate the insights that they captured about their customers' usage patterns, product performance behaviors, and overall market trends to transform their business models
C. The Business Metamorphosis phase helps drive an organization's core business model through the analytic insights gathered as the organization traverses the Big Data Business Model Maturity Index
D. Business Metamorphosis exercise can uncover Big Data requirements around decisions, analytics and data sources that can be leveraged to transform or metamorphose your organization's business model
E. All of the above

Answer: E

Explanation:
Business Metamorphosis is the most advanced phase in the Big Data Business Model Maturity Index (BDBMMI), where organizations fundamentally transform their business models through analytics-driven insights.
Option A: Correct. This phase helps organizations identify big data requirements related to decisions, analytics, and sources that drive business transformation.
Option B: Correct. Organizations integrate customer usage patterns, product behaviors, and market trends into their decision-making to redesign or innovate their business model.
Option C: Correct. Business Metamorphosis ensures that the core business model evolves continuously, guided by insights derived across maturity stages.
Since all are correct, the best answer is Option E (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Business Applications of Data Science: Big Data Business Model Maturity Index.

NEW QUESTION # 28
Which of the following is the most important part of Hadoop?

A. Hadoop Distributed File System (HDFS)
B. Spark Framework
C. Both B and C
D. Both A and B
E. MapReduce Framework

Answer: D

Explanation:
The Hadoop ecosystem consists of multiple components, but the two core components that define Hadoop are:
HDFS (Hadoop Distributed File System): Provides fault-tolerant, scalable storage across distributed clusters.
It is the backbone for storing massive datasets in a distributed fashion.
MapReduce Framework: Provides the parallel computing and data processing layer in Hadoop, enabling batch analysis over distributed datasets.
Option A: Correct, HDFS is essential.
Option B: Correct, MapReduce is essential.
Option C: Incorrect, Spark is a newer processing framework, but it is not originally part of Hadoop core.
Option D: Correct answer since both HDFS and MapReduce are considered the fundamental parts of Hadoop.
Option E: Incorrect, because Spark is not a core Hadoop component (though it integrates with Hadoop).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Big Data Ecosystems: Hadoop Architecture & Components.

NEW QUESTION # 29
......

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Free PDF DASCA - SDS Pass-Sure Frenquent Update

Valid Test SDS Format | SDS Most Reliable Questions

DASCA Senior Data Scientist Sample Questions (Q24-Q29):

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