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EMC DEA-7TT2 exam is an Associate-level certification exam for professionals seeking to validate their skills and knowledge in the field of Data Science and Big Data Analytics. DEA-7TT2 exam is designed to test candidates' understanding of the fundamental concepts and principles of data analysis, statistical modeling, and machine learning, with a focus on practical applications in real-world scenarios.
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EMC DEA-7TT2 program is an updated version of the previous EMC DEA-7TT1 certification. With the new test program, candidates can expect a more up-to-date curriculum that is more aligned with current industry standards and demands. Associate - Data Science and Big Data Analytics v2 Exam certification exam covers critical topics such as machine learning, artificial intelligence, data warehousing, data integration, and data analysis. The program also emphasizes the importance of collaboration, communication, and the ability to work effectively in a team for successful implementation of data analytics projects.
NEW QUESTION # 162
What is an appropriate data visualization to use in a presentation to a project sponsor?
Response:
Answer: B
NEW QUESTION # 163
Data has been collected on visitors' viewing habits at a bank's website. Which technique is used to identify pages commonly viewed during the same visit to the website?
Response:
Answer: C
NEW QUESTION # 164
You have been assigned to do a study of the daily revenue effect of a pricing model of online transactions. All the data currently available to you has been loaded into your analytics database; revenue data, pricing data, and online transaction data.
You find that all the data comes in different levels of granularity. The transaction data has timestamps (day, hour, minutes, seconds), pricing is stored at the daily level, and revenue data is only reported monthly.
What is your next step?
Response:
Answer: B
NEW QUESTION # 165
How is dimensionality defined in a "bag of words" document representation?
Response:
Answer: B
NEW QUESTION # 166
A study was run to identify general dietary patterns among the residents of a small town. Twelve thousand people were surveyed and the data was subject to K-means clustering. In one of the iterations, there were six clusters formed with 38, 1560, 1799, 2560, 2893, and 3150 respondents.
What should be the next step in identifying optimal clusters?
Response:
Answer: A
NEW QUESTION # 167
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