Jerry Nelson Jerry Nelson's Profile Page

Jerry Nelson Jerry Nelson

0 Course Enrolled • 0 Course Completed

Biography

ActualTestsIT DASCA SDS Different Formats

Our SDS learning guide beckons exam candidates around the world with our attractive characters. Our experts made significant contribution to their excellence. So we can say bluntly that our SDSsimulating exam is the best. Our effort in building the content of our SDS Study Materials lead to the development of learning guide and strengthen their perfection. You may find that there are always the latest information in our SDS practice engine and the content is very accurate.

We provide a wide range of learning and preparation methodologies to the customers for the SDS complete training. After using the SDS products, success would surely be the fate of customer because, self-evaluation, highlight of the mistakes, time management and sample question answers in comprehensive manner, are all the tools which are combined to provide best possible results. We are also offering 100% money back guarantee to the customers in case they don't achieve passing scores in the DASCA SDS in the first attempt.

>> SDS Pass4sure Pass Guide <<

SDS Study Guide Pdf, SDS Sample Questions Pdf

You can free download part of ActualTestsIT's practice questions and answers about DASCA Certification SDS Exam online. Once you decide to select ActualTestsIT, ActualTestsIT will make every effort to help you pass the exam. If you find that our exam practice questions and answers is very different form the actual exam questions and answers and can not help you pass the exam, we will immediately 100% full refund.

DASCA Senior Data Scientist Sample Questions (Q20-Q25):

NEW QUESTION # 20
Image files can be broken down into two broad categories:
i. Rasterized
ii. Vectorized
iii. Sectorized

A. ii, iii
B. i, ii
C. None of the above
D. i, iii

Answer: B

Explanation:
Images are broadly categorized based on how they store visual information:
Rasterized images (Option i):
Composed of a grid of pixels (bitmap).
Each pixel has color information.
Examples: JPEG, PNG, BMP.
Best for photos or complex visuals.
Vectorized images (Option ii):
Composed of paths defined by mathematical formulas.
Scalable without quality loss.
Examples: SVG, EPS, AI.
Best for logos, icons, and illustrations.
Sectorized images (Option iii):
Not a standard category in computer graphics.
Thus, image files are categorized into Rasterized and Vectorized, making Option A (i, ii) correct.
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Data Types & Multimedia Data Management.

NEW QUESTION # 21
Spark programs can be written in:

A. Java
B. All of the above
C. None of the above
D. Scala
E. Python

Answer: B

Explanation:
Apache Spark supports multiple programming languages for developing distributed applications:
Java (Option A): Supported through Spark's JVM-based APIs.
Scala (Option B): Spark is natively written in Scala, and Scala APIs provide full functionality.
Python (Option C): Supported via PySpark, enabling Python developers to leverage Spark.
Additionally, Spark also supports R and SQL-like queries, making it versatile for data scientists and engineers.
Thus, the correct answer is Option D (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming Tools: Spark APIs for Java, Scala, Python, and R.

NEW QUESTION # 22
ARIMA model is:

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

Answer: C

Explanation:
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).

NEW QUESTION # 23
Which of these are open-source column-oriented databases?

A. Cassandra
B. HBase
C. All of the above
D. Accumulo
E. Both A and B

Answer: C

Explanation:
Column-oriented databases store data by columns rather than by rows, enabling efficient queries over large datasets, especially in analytical workloads.
Cassandra (Option A): An open-source, highly scalable, distributed column-oriented NoSQL database.
HBase (Option B): An open-source, Hadoop-based, column-family NoSQL database modeled after Google BigTable.
Accumulo (Option C): An open-source, secure, sorted, distributed key/value store built on top of HDFS and based on Google BigTable.
Since all three (A, B, and C) are open-source column-oriented databases, the correct answer is Option E (All of the above).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Big Data Fundamentals: Columnar Databases & NoSQL Ecosystem.

NEW QUESTION # 24
Which of the following is main Machine Learning Library in Python?

A. SciPy
B. Matplotlib
C. Scikit-learn
D. None of the above
E. NumPy

Answer: C

Explanation:
Python supports multiple libraries for scientific computing and data analysis, but the primary machine learning library is:
Scikit-learn (Option B): Provides a wide range of machine learning algorithms for classification, regression, clustering, model evaluation, and preprocessing. It is the core ML library in Python.
NumPy (Option A): Provides numerical computing and array operations, essential for ML but not a machine learning library itself.
Matplotlib (Option C): Used for data visualization.
SciPy (Option D): Supports scientific computing and numerical methods, not focused on ML models.
Therefore, the correct answer is Option B (Scikit-learn).
Reference:
DASCA Data Scientist Knowledge Framework (DSKF) - Programming for Data Science: Python Libraries for Machine Learning.

NEW QUESTION # 25
......

You can conveniently test your performance by checking your score each time you use our DASCA SDS practice exam software (desktop and web-based). It is heartening to announce that all ActualTestsIT users will be allowed to capitalize on a free DASCA SDS Exam Questions demo of all three formats of the DASCA SDS practice test.

SDS Study Guide Pdf: https://www.actualtestsit.com/DASCA/SDS-exam-prep-dumps.html

If you are used to study with paper-based materials you can choose the PDF version of our SDS study guide, Especially for SDS Study Guide Pdf - Senior Data Scientist, Security & Privacy Our complete list of products including SDS exam product is protected and free from all the Trojans and viruses, Our IT experts check the updating of SDS Study Guide Pdf - Senior Data Scientist exam questions every day to ensure the high accuracy of our SDS Study Guide Pdf - Senior Data Scientist exam pdf.

Do you want to be this generation's Bill Gates, The development team prepares one or two examples with some variations, If you are used to study with paper-based materials you can choose the PDF version of our SDS Study Guide.

2025 100% Free SDS –Valid 100% Free Pass4sure Pass Guide | SDS Study Guide Pdf

Especially for Senior Data Scientist, Security & Privacy Our complete list of products including SDS exam product is protected and free from all the Trojans and viruses.

Our IT experts check the updating of Senior Data Scientist exam questions every day to ensure the high accuracy of our Senior Data Scientist exam pdf, Secondly, we support Credit Card payment for SDS test dump; your money will be safe surely.