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DASCA Senior Data Scientist Sample Questions (Q12-Q17):

NEW QUESTION # 12
OCR (Optical Character Recognition) is an application used for:

A. Machine learning
B. Big Data Analytics
C. MapReduce
D. Data mining

Answer: A

Explanation:
Optical Character Recognition (OCR) is the process of automatically recognizing and converting different types of documents - such as scanned paper documents, PDFs, or images - into editable and searchable text.
OCR systems use Machine Learning (ML) and Computer Vision techniques to detect and classify patterns of characters in images.
Algorithms like Convolutional Neural Networks (CNNs) are commonly used for image-based OCR.
While OCR may indirectly contribute to data mining or big data workflows, the core application is based on machine learning, where models are trained to classify and recognize text patterns.
Thus, OCR is primarily a Machine Learning application, making Option B correct.
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Applications of Machine Learning: OCR and Pattern Recognition.

NEW QUESTION # 13
JSON takes hierarchical data structures and serializes them into:

A. None of the above
B. Any desired format
C. Plain text format
D. Plain string format
E. Both A and B

Answer: E

Explanation:
JSON (JavaScript Object Notation) is a lightweight data-interchange format widely used for storing and exchanging structured or semi-structured data. JSON allows hierarchical (tree-like) structures, such as nested objects and arrays, to be serialized into a textual representation.
Option A (Plain text format): Correct. JSON files are stored as plain text, making them human-readable and language-independent.
Option B (Plain string format): Correct. JSON objects are transmitted as strings across networks (e.g., via APIs, RESTful services).
Option C: Incorrect. JSON does not serialize into "any format," but specifically into text/string-based formats.
Option D: Correct. Since JSON is both plain text and transmitted as string format, the right answer is both A and B.
Option E: Incorrect.
Thus, JSON serializes hierarchical data into plain text and string formats.
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Data Engineering Tools: Data Serialization Formats (JSON, XML, Avro).

NEW QUESTION # 14
Which of the following is NOT a process of Use Case?

A. Identify your key business stakeholders
B. Brainstorm the outcomes that the key stakeholders need to answer to facilitate making the decisions
C. Capture the decisions that the key business stakeholders need to make in order to support the organization's key business initiatives
D. Understand your organization's key business initiatives or business challenge
E. Brainstorm the questions that the key stakeholders need to answer to facilitate making the decisions

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 # 15
Which of the following is correct about customer lifetime value (CLTV)?
i. Most organizations determine the current customer lifetime value (CLTV) based on historic sales over past
12 to 18 months
ii. The goal of the CLTV score is to help marketing and store personnel to determine the "value" of a customer

A. Only i
B. Both i and ii
C. Only ii

Answer: B

Explanation:
Customer Lifetime Value (CLTV) is a predictive metric estimating the total revenue a business can reasonably expect from a customer during their entire relationship.
Statement i: Correct. Many organizations calculate CLTV using historic transactional data, often looking at sales records over the past 12-18 months to establish baselines.
Statement ii: Correct. The primary purpose of CLTV is to help marketing, sales, and retail teams understand customer value, enabling them to allocate budgets effectively for retention, promotions, and personalized marketing.
Thus, both statements are correct # Option C (Both i and ii).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Business Applications of Data Science: CLTV Metrics and Marketing Analytics.

NEW QUESTION # 16
Which classification steps are performed in inductive techniques?
i. Training Step
ii. Test Step
iii. Validation Step
iv. Application Step

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

Answer: B

Explanation:
Inductive learning techniques in machine learning (such as decision trees, neural networks, or SVMs) follow a systematic sequence of steps for classification:
Training Step (i): A model is built using training data, where the system learns relationships between features and target labels.
Test Step (ii): The trained model is evaluated on unseen test data to measure its performance and generalizability.
Validation Step (iii): Often, a validation set is used to fine-tune model parameters, avoid overfitting, and choose the best model configuration.
Application Step (iv): The final validated model is applied to classify new, real-world data.
Since all four steps (i, ii, iii, iv) are essential to inductive classification, the correct answer is Option D (i, ii, iii, iv).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Analytics & Machine Learning: Classification and Inductive Learning Techniques.

NEW QUESTION # 17
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