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Well D-DS-FN-23 Prep, Exam D-DS-FN-23 Certification Cost

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

Topic
Details

Topic 1

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 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

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 5

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.

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EMC Dell Data Science Foundations Sample Questions (Q92-Q97):

NEW QUESTION # 92
Which characteristic applies mainly to Data Science as opposed to Business Intelligence?

A. Data dashboards
B. Robust reporting
C. Focus on structured data
D. Advanced analytical methods

Answer: D

NEW QUESTION # 93
You are testing two new weight-gain formulas for puppies. The test gives the results: Control group: 1% weight gain Formula A. 3% weight gain Formula B. 4% weight gain A one-way ANOVA returns a p-value = 0.027
What can you conclude?

A. Formula A and Formula B are about equally effective at promoting weight gain.
B. Either Formula A or Formula B is effective at promoting weight gain.
C. Formula B is more effective at promoting weight gain than Formula A.
D. Formula A and Formula B are both effective at promoting weight gain.

Answer: B

NEW QUESTION # 94
You have an automotive database containing numeric characteristics such as engine size, horsepower, and top speed.
Which technique could you use to group similar cars together?

A. Naïve Bayes classifier
B. Logistic regression
C. K-means clustering
D. Association rules

Answer: C

NEW QUESTION # 95
Which phase of the data analytic lifecycle includes conducting project sponsor interviews and drafting a problem statement?

A. Operationalize
B. Model planning
C. Discovery
D. Model building

Answer: C

Explanation:
The Discovery phase involves understanding the business problem by conducting project sponsor interviews, gathering requirements, and drafting a problem statement to define the analytic objectives clearly.

NEW QUESTION # 96
The web analytics team uses Hadoop to process access logs. They now want to correlate this data with structured user data residing in their massively parallel database.
Which tool should they use to export the structured data from Hadoop?

A. Sqoop
B. Scribe
C. Pig
D. Chukwa

Answer: A

NEW QUESTION # 97
......

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