ACT350: CH10 Exam 2
The acronym ETL, in the process of readying data for use in data analysis, refers to what three words? A. Extrapolate, transform, and learn B. Extrapolate, transpose, and load C. Extract, transform, and load D. Extract, transform, and learn
C
Which type of question does descriptive analysis address? A. What should we do based on what we expect will happen? B. Why did it happen? C. What happened? D. Will it happen in the future?
C
ADS is a standard format for data files and fields typically needed to support an external audit in a given financial business process area that was developed by the AICPA. The acronym ADS stands for what three words? A. Audit Data Standards B. Auditor Data Standards C. Accounting Data Standards D. Accounting Doctoral Scholars
A
If we wanted to know what grade we needed to get on the final in this class based on our expected performance before the final, we would call that _____________ analysis? A. Prescriptive B. Diagnostic C. Predictive D. Descriptive
A
What type of analysis addresses questions of "Why did it happen"? Multiple Choice Diagnostic analysis Predictive analysis Descriptive analysis Prescriptive analysis
A
What type of analysis would address the question of whether a customer will ultimately pay if credit is granted? A. Predictive analysis B. Prescriptive analysis C. Descriptive analysis D. Diagnostic analysis
A
Which type of question does prescriptive analysis address? A. What should we do based on what we expect will happen? B. What happened? C. Will it happen in the future? D. Why did it happen?
A
According to estimates considered in the chapter, up to what percentage of a data analyst's time is spent cleaning (or scrubbing) the data to be ready for analysis? A. 0 percent B. 90 percent C. 20 percent D. 40 percent
B
Which term is used to describe the science of examining raw data, removing excess noise from the dataset, and organizing the data with the purpose of drawing conclusions for decision making? A. Audit Analytics B. Data Analytics C. Extract, transform, and load D. Big Data
B
Big Data is often described by the 4 Vs, or: A. volume, volatility, veracity and variety. B. volume, velocity, veracity, and variability. C. volume, volatility, veracity, and variability. D. volume, velocity, veracity, and variety.
D
