AUTHORITATIVE RELIABLE D-DS-FN-23 EXAM TEST PROVIDE PREFECT ASSISTANCE IN D-DS-FN-23 PREPARATION

Authoritative Reliable D-DS-FN-23 Exam Test Provide Prefect Assistance in D-DS-FN-23 Preparation

Authoritative Reliable D-DS-FN-23 Exam Test Provide Prefect Assistance in D-DS-FN-23 Preparation

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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
  • 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 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.
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.

EMC Dell Data Science Foundations Sample Questions (Q285-Q290):

NEW QUESTION # 285
A disk drive manufacturer has a defect rate of less than 1.0% with 98% confidence. A quality assurance team samples 1000 disk drives and finds 14 defective units.
Which action should the team recommend?

  • A. A larger sample size should be taken to determine if the plant is functioning properly
  • B. The manufacturing process is functioning properly and no further action is required.
  • C. The manufacturing process should be inspected for problems.
  • D. A smaller sample size should be taken to determine if the plant is functioning properly

Answer: C


NEW QUESTION # 286
What is holdout data?

  • A. a subset of the provided data set selected at random and used to validate the model
  • B. a subset of the provided data set selected at random and used to initially construct the model
  • C. a subset of the provided data set that is removed by the data scientist because it contains outliers
  • D. a subset of the provided data set that is removed by the data scientist because it contains data errors

Answer: A


NEW QUESTION # 287
Which visualization technique should be avoided?

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

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 # 288
Refer to the exhibit.

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

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

Answer: D


NEW QUESTION # 289
What is part of the model output for a linear regression?

  • A. Coefficients indicating relative impact of the input variables on the outcome
  • B. The assignment of each input datum to a cluster
  • C. The set of all rules X -> Y with minimum support and confidence
  • D. Probability score for each possible class label

Answer: A

Explanation:
In linear regression, the model output includes coefficients that indicate the relative impact of the input variables on the outcome. These coefficients represent how much each input variable influences the predicted outcome.


NEW QUESTION # 290
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