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最新的 DASCA Data Scientist SDS 免費考試真題 (Q10-Q15):

問題 #10
Which of the following is NOT a valid section of Big Data Strategy document?

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

答案：B

解題說明：
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.

問題 #11
Tar is an example of:

A. Archive file format
B. None of the above
C. CSV file format
D. ARV file format
E. Text file format

答案：A

解題說明：
TAR (Tape Archive) is a widely used archive file format in Unix/Linux environments. It is used to combine multiple files into a single archive file (with extension .tar).
Option A: Correct. TAR is specifically designed for archiving.
Option B (CSV): Incorrect. CSV (Comma-Separated Values) is a tabular text data format.
Option C (ARV): Incorrect - no such format.
Option D (Text): Incorrect. Though TAR may contain text files, the TAR format itself is not plain text but an archive format.
Option E: Incorrect since Option A is valid.
Thus, TAR is an Archive file format.
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Data Storage Formats in Data Science & Engineering.

問題 #12
ARIMA model is:

A. Autoregressive moving average
B. All of the above
C. Autoresponsive moving average
D. Autoreactive moving average
E. Autointeractive moving average

答案：A

解題說明：
ARIMA stands for AutoRegressive Integrated Moving Average, one of the most widely used models for time series forecasting.
AutoRegressive (AR): Model uses past values of the variable to predict future values.
Integrated (I): Differencing is applied to make the time series stationary.
Moving Average (MA): Model incorporates past forecast errors into predictions.
Option B: Correct - autoregressive + moving average is part of ARIMA's name.
Options A, C, D: Incorrect because these terms are not recognized statistical modeling frameworks.
Option E: Incorrect, since only B is valid.
Thus, the correct answer is Option B.
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Analytics: Time Series Models (AR, MA, ARIMA).

問題 #13
OCR (Optical Character Recognition) is an application used for:

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

答案：C

解題說明：
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.

問題 #14
Which of the following is CORRECT?
i. CDMO should NOT own the data lake, the data warehouse, or any of the underlying data architecture or technologies.
ii. CDMO should own the data lake, the data warehouse, or any of the underlying data architecture or technologies.
iii. CIO should NOT own the data lake, the data warehouse, or any of the underlying data architecture or technologies.
iv. CIO should own the data lake, the data warehouse, or any of the underlying data architecture or technologies.

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

答案：D

解題說明：
The Chief Data Monetization Officer (CDMO) is responsible for driving value extraction from data assets, not owning infrastructure. By contrast, the Chief Information Officer (CIO) traditionally owns technology infrastructure, including data lakes, warehouses, and data architectures.
Statement i: Correct. CDMO should NOT own data infrastructure. Their role is strategic - monetizing insights, not managing systems.
Statement ii: Incorrect. CDMO focuses on monetization, not architecture ownership.
Statement iii: Incorrect. CIO indeed does own these systems.
Statement iv: Correct. CIO owns the data lake, data warehouse, and underlying architectures/technologies.
Thus, the correct combination is i and iv # Option C.
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Roles in Data Leadership: CIO vs CDMO.

問題 #15
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