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DASCA Senior Data Scientist Sample Questions (Q79-Q84):

NEW QUESTION # 79
Which of the following is NOT a valid section of Big Data Strategy document?

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

Answer: C

Explanation:
A Big Data Strategy document provides a framework for aligning data initiatives with organizational objectives. It typically includes:
Business strategy (Option A): Ensures that big data initiatives align with overall corporate strategy.
Key decisions (Option B): Identifies the decisions data will help optimize or automate.
Key business initiatives (Option D): Links big data projects with critical organizational initiatives.
Key business entities (Option E): Defines the core entities (customers, products, channels) around which data will be organized.
However:
Business decisions (Option C): This is redundant and not a standard section; "key decisions" covers this aspect already.
Thus, the correct answer is Option C (Business decisions).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Big Data Strategy and Business Alignment.

NEW QUESTION # 80
The Big Data Vision Workshop process is ideal for organizations who:

A. All of the above
B. Have a wealth of data that they do not know how to monetize
C. Both A and B
D. Have a desire to leverage Big Data to transform their business but do not know where and how to start
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: 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 # 81
Which of the following phases is NOT a Big Data Business Model Maturity Index?

A. Data Monetization
B. Business Metamorphosis
C. Business Strategy
D. Business Monitoring
E. Business Optimization

Answer: C

Explanation:
The Big Data Business Model Maturity Index (BDBMMI) defines phases organizations pass through in leveraging data strategically:
Business Monitoring (A): Tracking metrics and reporting.
Business Insights (not listed in options but part of the framework).
Business Optimization (B): Using analytics to improve efficiency.
Data Monetization (D): Creating new revenue streams with data.
Business Metamorphosis (E): Transforming the business model through data.
Business Strategy (Option C): While strategy is essential, it is not one of the defined phases of BDBMMI.
Thus, the correct answer is Option C (Business Strategy).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Big Data Business Model Maturity Index (BDBMMI).

NEW QUESTION # 82
Exploratory analytic algorithms help the Data Science team to better:

A. All of the above
B. Understand the data content
C. Understand patterns in the data
D. Both A and B
E. Gain a high-level understanding of relationships

Answer: A

Explanation:
Exploratory analytics (often referred to as Exploratory Data Analysis - EDA) is a fundamental step in data science, enabling practitioners to discover initial insights, detect anomalies, and understand the structure of datasets before applying predictive or prescriptive modeling.
Option A (Understand the data content): Correct. EDA techniques (descriptive statistics, summary tables, profiling) reveal missing values, data types, and distributions.
Option B (Gain a high-level understanding of relationships): Correct. Correlation analysis, scatter plots, and cross-tabulations help identify dependencies between variables.
Option C (Understand patterns in the data): Correct. Visualization and clustering methods help discover hidden structures, seasonalities, and outliers.
Since exploratory algorithms contribute to all of these objectives, the correct answer is Option E (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Analytics and Machine Learning: Exploratory Analytics & EDA.

NEW QUESTION # 83
Semi-structured data does NOT include:

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

Answer: B

NEW QUESTION # 84
......

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