Free DASCA SDS Questions

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DASCA Senior Data Scientist Sample Questions (Q16-Q21):

NEW QUESTION # 16
What is TRUE for "rehashing"?

Answer: B

Explanation:
Rehashing is a technique used in dynamic hash tables when the load factor (ratio of entries to bucket size) exceeds a certain threshold. It ensures efficient lookup, insertion, and deletion operations.
Option A (Correct): A larger hash table is allocated in memory to accommodate more entries.
Option B (Correct): A new hash function is typically required to map keys into the expanded table range.
Option C (Correct): All key-value pairs from the old table are re-inserted (rehashed) into the new table using the new hash function.
Since all three conditions (A, B, and C) are true, the best choice is Option E (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming for Data Science: Data Structures & Hashing Techniques


NEW QUESTION # 17
Spark is written in:

Answer: A

Explanation:
Apache Spark is an open-source distributed computing framework widely used for big data processing and machine learning pipelines.
The core implementation of Spark is written in Scala (Option A), which runs on the JVM (Java Virtual Machine).
Spark also provides APIs for Java, Python (PySpark), R, and SQL, but its native language is Scala.
Options C (C) and D (C++) are incorrect; Spark is not written in these languages.
Python (Option E) is a supported API, but Spark itself is not written in Python.
Thus, the correct answer is Scala (Option A).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming Tools for Big Data & Distributed Computing.


NEW QUESTION # 18
ElementTree sub-library gives us direct access to:

Answer: E

Explanation:
In Python, the ElementTree module (part of the standard library xml.etree.ElementTree) provides a simple and efficient API for parsing and creating XML data.
The main feature of ElementTree is its ability to provide direct access to the parse tree of an XML document.
This allows developers to:
Parse XML into an in-memory tree structure.
Traverse, search, modify, and extract information from XML elements.
Write back changes into XML files.
Options B, C, and D (Delete, Copy, Insert tree) are not standard terminology in XML handling with ElementTree. While you can delete, insert, or copy elements, the module itself primarily gives parse tree access.
Thus, the correct answer is Option A (Parse tree of the XML).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming for Data Science: XML/JSON Handling in Python.


NEW QUESTION # 19
Which of the following is NOT a process of Use Case?

Answer: B

Explanation:
Use Case Development in data science projects involves identifying business needs and mapping analytics to business decisions. The standard steps include:
Option A: Understanding the key initiatives or challenges.
Option B: Identifying the key stakeholders.
Option C: Capturing the decisions stakeholders must make.
Option E: Brainstorming the questions stakeholders need answered to support decisions.
However:
Option D (Brainstorm the outcomes stakeholders need to answer): Incorrect phrasing. It is not "outcomes" that are brainstormed but questions and decisions.
Thus, the correct answer is Option D.
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Business Use Case Development Process.


NEW QUESTION # 20
Which of the following is True about Time Series Analysis?

Answer: B

Explanation:
Time Series Analysis (TSA) is the process of analyzing data collected sequentially over time to extract meaningful insights.Applications include:
Option A: Correct. Event prediction (e.g., failure detection in IoT or predictive maintenance).
Option B: Correct. Forecasting future values (e.g., stock price, sales forecasting).
Option C: Correct. Pattern discovery in large-scale time series datasets using clustering, anomaly detection, or seasonality detection.
Since all three are true, the best answer is Option E (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Analytics and Machine Learning: Time Series Analysis and Forecasting.


NEW QUESTION # 21
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