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

Topic	Details
Topic 1	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 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	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.
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	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 (Q331-Q336):

NEW QUESTION # 331
Based on the exhibit, what is a likely issue with the data?

A. Incomplete data; indicating potential issues with data transmission
B. No obvious concerns with the data is visible
C. Saturated data; indicating potential issues with data definitions
D. Mis-scaled data; indicating potential issues with data entry

Answer: C

NEW QUESTION # 332
What is an appropriate data visualization to use in a presentation for an analyst audience?

A. Pie chart
B. Area chart
C. Stacked bar chart
D. ROC curve

Answer: D

NEW QUESTION # 333
What activities occur during the discovery phase of the data analytics lifecycle?

A. Build training and test datasets
B. Perform ETL and data exploration
C. Deploy and monitor model performance
D. Interview project sponsor and stakeholders

Answer: D

NEW QUESTION # 334
In linear regression modeling, which action can be taken to improve the linearity of the relationship between the dependent and independent variables?

A. Use a different statistical package
B. Apply a transformation to a variable
C. Calculate the R-Squared value
D. Change the units of measurement on the independent variable

Answer: B

NEW QUESTION # 335
Which relationship holds for a confusion matrix?

A. Recall = 1 - False Negative Ratio
B. Recall = 1 - False Positive Ratio
C. Precision = 1 - False Negative Ratio
D. Precision = 1 - False Positive Ratio

Answer: A

NEW QUESTION # 336
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