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Title: Reliable D-DS-FN-23 Test Objectives | D-DS-FN-23 Detail Explanation [Print This Page]
Author: willsto788    Time: yesterday 17:24
Title: Reliable D-DS-FN-23 Test Objectives | D-DS-FN-23 Detail Explanation
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EMC D-DS-FN-23 Exam Syllabus Topics:
TopicDetails
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
  • 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.

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EMC Dell Data Science Foundations Sample Questions (Q95-Q100):NEW QUESTION # 95
In a Logistic Regression, the coefficient for "age" equals -3.
What is the correct interpretation of the Logistic Regression coefficient, holding all other variables constant?
Answer: D

NEW QUESTION # 96
A data scientist is asked to implement an article recommendation feature for an online magazine. The magazine does not want to use client tracking technologies such as cookies or reading history.
Therefore, only the style and subject matter of the current article is available for making recommendations.
All of the magazine's articles are stored in a database in a format suitable for analytics.
Which method should the data scientist try first?
Answer: B

NEW QUESTION # 97
Consider a scale that has five (5) values that range from "not important" to "very important".
Which data classification best describes this data?
Answer: B

NEW QUESTION # 98
You have created a Logistic Regression model to predict customer churn for your company. The company's Marketing department wants to use your model to identify at-risk customers and offer incentives to keep them from leaving.

Using two different thresholds for the model provides the two confusion matrices shown in the graphic.
Marketing understands the relative costs of missing at-risk customers versus offering incentives to customers who are not at risk. Therefore, you need their advice on how to set the appropriate threshold on the churn model.
You are meeting with the Marketing team. In the meeting, you plan to state: "Raising the threshold from 0.5 to 0.75 reduces the number of unnecessary incentives that can be offered, at the cost of missing more of the customers who churned." What is the most appropriate visual to reinforce this statement?
Answer: C

NEW QUESTION # 99
You have been assigned to do a study of the daily revenue effect of a pricing model of online transactions.
You have tested all the theoretical models in the previous model planning stage, and all tests have yielded statistically insignificant results.
What is your next step?
Answer: C

NEW QUESTION # 100
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