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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 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.
Topic 3
- 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 4
- 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 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 (Q21-Q26):
NEW QUESTION # 21
You have been assigned to perform a study of the daily revenue effect of a pricing model of online transactions. All data currently available to you has been loaded into your analytics database. This includes revenue data, pricing data, and online transaction data.
You discover that all data comes in different levels of granularity. The transaction data has timestamps consisting of day, hour, minutes, and seconds. Pricing is stored at the daily level and revenue data is only reported monthly.
What is the next step?
- A. Disregard revenue as the key reason in the pricing model and create a daily model based on pricing and transactions only.
- B. Aggregate all data to the monthly level in order to create a monthly revenue model.
- C. Interpolate a daily model for revenue from the monthly revenue data.
- D. Report back to the business owner that the current data model does not support the business question.
Answer: D
NEW QUESTION # 22
You submit a MapReduce job to a Hadoop cluster. Although the job was successfully submitted, you notice that it is not completing.
What should be done?
- A. Ensure that the TaskTracker is running
- B. Ensure that the NameNode is running
- C. Ensure that the JobTracker is running
- D. Ensure that a DataNode is running
Answer: A
NEW QUESTION # 23
Refer to the Exhibit.
You are going into a meeting where you anticipate your manager will have a question on your dataset.
Specifically, your manager will want to know about customers that are classified as renters with a good credit status.
In order to prepare for the meeting, you create a rule: RENTER => GOOD CREDIT.
What is the confidence of this rule?
- A. 63%
- B. 41%
- C. 18%
- D. 73%
Answer: A
NEW QUESTION # 24
Which participant in a data analytics project is typically responsible for assessing the validity of the model?
- A. Project sponsor
- B. Business user
- C. Project manager
- D. Data scientist
Answer: D
NEW QUESTION # 25
Refer to the exhibit.
What provides the decision tree for predicting whether or not someone is a good or bad credit risk.
What would be the assigned probability, p(good), of a single male with no known savings?
- A. 0.83
- B. 0.6
- C. 0
- D. 0.498
Answer: A
NEW QUESTION # 26
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