Chapter 1 Data Analytics in Accounting and Business
1) Data analytics is the process of evaluating data with the purpose of drawing
conclusions to address business questions.
2) The process of data analytics aims to transform raw information into data to create
value.
3) Data analytics has the potential to transform the manner in which companies run their
businesses; however, it is not practical in the near future.
4) Auditors can use social media to hear what customers are saying about a company and
compare this to inventory obsolescence and other estimates.
5) Data analytics allows auditors to glean insights that are beneficial to the client, without
breaching independence.
6) The predictive analytics is an important aspect of data analytics for auditors, but is not
applicable for tax accountants.
7) The I in IMPACT Cycle represents Identify the Question.
8) The M in IMPACT Cycle represents Master the Data.
9) The P in IMPACT Cycle represents Predict the Results.
10) The A in IMPACT Cycle represents Analyze the Data.
11) The C in IMPACT Cycle represents Continuously Track.
12) The T in IMPACT Cycle represents Track Outcomes.
13) Data normalization can reduce data redundancy and improve data integrity.
14) The IMPACT cycle is iterative, as insights are gained, outcomes are tracked, and new
questions are identified.
15) Data analytics professionals estimate that they spend between 25 percent and 70
percent of their time cleaning data so it can be analyzed.
16) Data analysis through data manipulation is performing basic analysis to understand
the quality of the underlying data and its ability to address the business question.
17) To be proficient in data analysis, accountants need to become data scientists.
,
,18) By developing an analytics mindset, accountants will be able to recognize when and
how data analytics can address business questions.
19) While it is important for accountants to clearly articulate the business problem,
drawing appropriate conclusions, based on the data, should be left to statisticians.
20) Analytic-minded accountants should report results of analysis in an accessible way to
each varied decision maker, along with their specific needs.
21) With a goal of giving organizations the information they need to make sound and
timely business decisions, data analytics often involves all of the following except:
A) technologies.
B) statistics.
C) growth.
D) databases.
22) Patterns discovered from ________ enable businesses to identify opportunities and
risks in order to better plan for ________.
A) past archives; the future
B) current data; the future
C) current data; today
D) past archives; today
23) Which of the following best describes the data analytics skill of descriptive data
analysis?
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that
allows enhanced analysis
D) comprehend the process needed to clean and prepare the data before analysis
24) Which of the following best describes the data analytics skill of data quality?
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) demonstrate the ability to sort, rearrange, merge, and reconfigure data in a manner that
allows enhanced analysis
D) comprehend the process needed to clean and prepare the data before analysis
25) Which of the following best describes the data analytics skill of data analysis through
data manipulation?
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) demonstrate ability to sort, rearrange, merge, and reconfigure data in a manner that
allows enhanced analysis
, D) comprehend the process needed to clean and prepare the data before analysis
26) Which of the following best describes the data analytics skill of data scrubbing and
data preparation?
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) demonstrate the ability to sort, rearrange, merge and reconfigure data in a manner that
allows enhanced analysis
D) comprehend the process needed to clean and prepare the data before analysis
27) Which of the following best describes the data analytics skill of developing an
analytics mindset?
A) recognize when and how data analytics can address business questions
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) recognize what is meant by data quality, be it completeness, reliability or validity
D) comprehend the process needed to clean and prepare the data before analysis
28) Which of the following best describes the data analytics skill of data visualization and
data reporting?
A) recognize when and how data analytics can address business questions
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) recognize what is meant by data quality, be it completeness, reliability or validity
D) report results of analysis in an accessible way to each varied decision maker and their
specific needs
29) Which of the following best describes the data analytics skill of defining and
addressing problems through statistical data analysis?
A) recognize what is meant by data quality, be it completeness, reliability or validity
B) perform basic analysis to understand the quality of the underlying data and its ability
to address the business question
C) demonstrate ability to sort, rearrange, merge and reconfigure data in a manner that
allows enhanced analysis
D) identify and implement an approach that will use statistical data analysis to draw
conclusions and make recommendations on a timely basis
30) While accountants don't need to become data scientists, they must know how to do
the following except:
A) Clearly articulate the business problem the company is facing
B) Communicate with the data scientists about specific data needs and understand the
underlying quality of the data
C) Build a data repository
D) Comprehend the process needed to clean and prepare the data before analysis