ABSOLUTE YOUR EXAM PREPARATION WITH EMC D-DS-FN-23 DUMPS

Absolute Your Exam Preparation With EMC D-DS-FN-23 Dumps

Absolute Your Exam Preparation With EMC D-DS-FN-23 Dumps

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EMC D-DS-FN-23 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Advanced Analytics for Big Data - Technology and Tools: This section of the exam measures the skills of a Data Science Enthusiast and addresses the technological challenges associated with Big Data. It introduces tools and technologies such as MapReduce, Hadoop, the Hadoop ecosystem, in-database analytics, SQL essentials, and advanced SQL techniques like window functions and MADlib.
Topic 2
  • Advanced Analytics - Theory, Application, and Interpretation of Results for Eight Methods: This section of the exam measures the skills of an Entry-Level Data Analyst and covers foundational knowledge in various advanced analytics methods. Topics include the theory, application, and interpretation of K-means clustering, association rules, linear and logistic regression, naïve Bayesian classifiers, decision trees, time series analysis, and text analytics.
Topic 3
  • Operationalizing an Analytics Project and Data Visualization Techniques: This section of the exam measures the skills of an Entry-Level Data Analyst and explains best practices for communicating findings and operationalizing analytics projects. It covers effective methods for presenting projects to various audiences and emphasizes the importance of planning and creating impactful data visualizations.

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EMC Dell Data Science Foundations Sample Questions (Q94-Q99):

NEW QUESTION # 94
Refer to the exhibit.

Which type of data issue would you suspect based on the exhibit?

  • A. Mis-scaled data, indicating potential issues with data entry
  • B. Incomplete data, indicating potential issues with data transmission
  • C. "Saturated" data, indicating potential issues with data definitions
  • D. The exhibit does not raise any obvious concerns with the data.

Answer: C


NEW QUESTION # 95
A Data Scientist is assigned to build a model from a reporting data warehouse. The warehouse contains data collected from many sources and transformed through a complex, multi-stage ETL process.
What is a concern the data scientist should have about the data?

  • A. It is too centralized
  • B. It is too processed
  • C. It is not structured
  • D. It is not normalized

Answer: B


NEW QUESTION # 96
A time series of monthly sales indicates a periodic pattern, and the value reaches the peak every December.
Which statistic needs to be subtracted from the actual value to adjust for this seasonal effect?

  • A. Average value for each month over a few years
  • B. Mean value of sales within each year
  • C. Least-squares-fit line of the series
  • D. Mean value of sales over the whole time series

Answer: A


NEW QUESTION # 97
Which word or phrase completes the statement; "Adata scientist would consider a RDBMS is to a table as R is to a_____."?

  • A. Matrix
  • B. List
  • C. Array
  • D. Data frame

Answer: D


NEW QUESTION # 98
Refer to the exhibit.

To predict whether or not a customer will renew their annual property insurance policy, an insurance company built and operationalized a naïve Bayes classification model.
Inthemodel, therearetwo classlabels, renewaland non-renewal, thatare assignedtoeachcustomerbased on their attributes. Asubset of the key attributes, their values, and corresponding conditional probabilities are provided in the exhibit.
A customer has the following attributes:
- Age is greater than 65 years
- Owns their own home
- Renewal month is August
If 20% of customers do not renew their policies every year, what is the score for a non-renewal in the naïve Bayesian model for the customer described above?

  • A. 0.0020
  • B. 0.0004
  • C. 0.0002
  • D. 0.0040

Answer: B


NEW QUESTION # 99
......

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