Data Analytics & AI Final Exam QUESTIONS AND ANSWERS
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Data Analytics & AI Final Exam QUESTIONS AND ANSWERS Data Analytics & AI Final Exam QUESTIONS AND ANSWERS Data Analytics & AI Final Exam QUESTIONS AND ANSWERS Data Analytics & AI Final Exam QUESTIONS AND ANSWERS Data Analytics & AI Final Exam QUESTIONS AND ANSWERS
Data Analytics & AI Final Exam
QUESTIONS AND ANSWERS
1. Descriptive analytics seeks to answer which questions?: What
happened? What is happening?
2. What are the questions that predictive analytics seek to answer?: What
will happen? Why will it happen?
3. What are the questions that prescriptive analytics seek to answer?: What
should I do? Why should I do it?
4. Data analytics in the retail value chain can only be used at the beginning
of the whole set of processes (with vendors) and at the end (with customers),
but not in the intervening stages
T or F: False
5. A DSS stands for?: decision support system
6. DBMS stands for?: database management system
7. BI stands for?: business intelligence
8. ERP stands for?: Enterprise Resource Planning
9. ETL stands for?: Extract Transform Load
10. DW stands for?: data warehousing
11. OLTP stands for?: Online Transactional Processing
12. Which is the best definition of data?: Digitized raw material, structured or
unstructured, for analytical systems
13. CRM stands for?: customer relationship management
14. SCM stands for?: supply chain management
1/9
, .
15. Data source reliability: Where did the data come from and why should we put
any trust in it?
16. Data accessibility/security: who had access to the data, and what evidence
do we have that it was manipulated?
17. Data Currency/timeliness: How new or old is the data, and what does that
mean for the project/question at hand?
18. Data Granularity: How precise is the data? How many places to the right of the
decimal?
19. Data validity and relevancy: Does the data measure what it is supposed to,
and how does it relate to the problem we are solving?
20. Data table entries for race, sex, gender: structured, categorical, nominal
21. Data table entries for temperature (C or F): Structured, numerical, interval
22. Data table entries for household income (1-low, 2-medium etc.): Structured,
categorical, ordinal
23. Image, audio, and video files: Unstructured, multimedia
24. All of the following actions (steps) are important in data preprocessing
EXCEPT?: data distribution
25 Skewness and kurtosis measure the distribution of data as depicted in a
graphed curve?
T or F: True
2/9
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