NEW D-DS-FN-23 TEST DURATION, UPDATED D-DS-FN-23 DEMO

New D-DS-FN-23 Test Duration, Updated D-DS-FN-23 Demo

New D-DS-FN-23 Test Duration, Updated D-DS-FN-23 Demo

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

TopicDetails
Topic 1
  • 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.
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
  • Data Analytics Lifecycle: This section of the exam measures the skills of an Entry-Level Data Analyst and explains the purpose and phases of the data analytics lifecycle. It includes understanding key activities and roles involved in the discovery, data preparation, model planning, and model building phases to successfully manage analytics projects.
Topic 4
  • Big Data, Analytics, and the Data Scientist Role: This section of the exam measures the skills of a Data Science Enthusiast and covers the basic concepts of Big Data, including its defining characteristics and the business drivers behind its rise. It also introduces the role of the Data Scientist, highlighting the critical skills needed in the data science field.
Topic 5
  • Initial Analysis of the Data: This section of the exam measures the skills of a Data Science Enthusiast and focuses on the first steps in analyzing data. It explains how basic R commands are used for exploration, discusses important statistical measures and visualizations, and describes hypothesis testing techniques for evaluating models.

EMC Dell Data Science Foundations Sample Questions (Q349-Q354):

NEW QUESTION # 349
Refer to the exhibit.

In the exhibit, a correlogram is provided based on an autocorrelation analysis of a sample dataset.
What can you conclude from only this exhibit?

  • A. There is significant autocorrelation through lag 3
  • B. Differencing is required before proceeding with any analysis
  • C. There is no structure left to model in the data
  • D. Lag 7 has a significant negative autocorrelation

Answer: A


NEW QUESTION # 350
Which word or phrase completes the statement? A spreadsheet is to a data island as a centralized database for reporting is to a __________?

  • A. Data Warehouse
  • B. Data Mart
  • C. Analytic Sandbox
  • D. Data Repository

Answer: A


NEW QUESTION # 351
Before you build an ARMA model, how can you tell if your time series is weakly stationary?

  • A. There appears to be a constant variance around a constant mean.
  • B. The series is normally distributed.
  • C. The mean of the series is close to 0.
  • D. There appears to be no apparent trend component.

Answer: A


NEW QUESTION # 352
Which visualization technique should be avoided?

  • A. Using visuals to illustrate key points
  • B. Achieving a high data-ink ratio
  • C. Using tables of numbers to present all of the data visually
  • D. Using a small number of contrasting colors to draw distinctions

Answer: C

Explanation:
Using tables of numbers to present all of the data visually should be avoided, as it can overwhelm the audience and make it harder to interpret key insights. Instead, visualizations should simplify data and focus on illustrating trends or patterns effectively.


NEW QUESTION # 353
Refer to the exhibit.

You have scored your Naive bayesian classifier model on a hold out test data for cross validation and determined the way the samples scored and tabluated them as shown in the exhibit.
What are the Precision and Recall rate of the model?

  • A. Precision =262/288 Recall = 262/277
  • B. Precision = 288/262 Recall = 277/262
  • C. Precision = 262/277 Recall = 262/288
  • D. Precision = 277/262 Recall = 288/262

Answer: C


NEW QUESTION # 354
......

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