EXAM 1 Flashcards
(217 cards)
1
Q
CH 1 (1.1-11.4)
A
2
Q
1.1 How are Data and Analytics Transforming the Accounting Profession?
A
3
Q
Performing data analytics includes 1) id___ both the 2) d___a necessary for the 3) an___ and the 4) ap____ analysis 5) m___
A
1) identifying
2) data
3) analysis.
4) appropriate
5) method
4
Q
The profession is experiencing the following changes:
-Efficiency from automation of routine accounting tasks
-journal entries
-financial reporting
-Professional examinations include topic of data and analytics
-Enhanced insight and analysis
A
5
Q
Define Data
1) r___ figures and 2) f__
A
1) raw
2) facts
6
Q
Technology helps convert that data to i_____
A
information
7
Q
Define Information
1) k___ gained from data that’s 2) re____ for 3) an___ purposes
A
1) knowledge
2) relevant
3) analysis
8
Q
Example of technology converting data to information
EX. A sales transaction
Sales transaction data will include the 1) d__ sold, the 2) pr___ purchased, 3) q___ sold, and 4) p___ for each sale.
-information is the total sales by product, which can then be used for analysis and decision making
A
1) date
2) product
3) quantity
4) price
9
Q
Define Data Analytics
the process of analyzing 1) r___ d__ to answer 2) ___ or provide 3) in___ts
A
1) raw data
2) questions
3) insights
10
Q
Define self-service business intelligence (SSBI) software
1) e__to use, 2) ac___ software that can 3) p__ data, 4) an__ data, and 5) re___ re___
it’s increase use of 6) d___ and a____
A
1) easy
2) accessible
3) prepare
4) analyze
5) report results
6) data and analytics
11
Q
What are the 2 key features of self-service business intelligence (SSBI) software?
-It provides 1) ex___ data processing capabilities for 2) pr____ data, 3) an___ data, and 4) re___ data an__ results
-It is 5) __ to use. No 6) d___e in computer science is required!
A
1) extended
2) preparing
3) analyzing
4) reporting data analysis
5) easy
6) degree
12
Q
Define null value
indicates an un___ or m___ value
not the same as ___
A
unknown or missing
not the same as zero
13
Q
Analytics and Auditing
-Audits have expanded beyond sample-based testing to include analyses of 1) en___ po____ of audit-relevant data.
-Auditors can review 2) e____ data sets to identify all 3) ex____, an____s, and out__
-Data driven audits 4) r__ the time the client spends gathering 5) i____ for the auditor and allows more 6) ___ for the analysis, making audits a 7) b___ experience for everyone involved.
A
1) entire population
2) entire
3) exceptions, anomalies, and outliers.
4) reduce
5) information
6) time
7) better
14
Q
Analytics and Auditing
Both 1) i___ and e___ auditors use 2) an__ to perform 3) ___ assessment and substantive 4) pr____
A
1) internal and external
2) analytics
3) risk
4) procedures
15
Q
Analytics and Auditing
Risk assessment helps the auditor quickly identify the accounts that appear to have a 1) h___ risk of misstatement, so they can 2) in___ further.
A
1) higher
2) investigate
16
Q
Audit and Analytics
In addition to risk assessment, auditors can use data analytics to perform 1) su___ an___ pro___ that 2) su___t the assertion that the financial 3) rec___ of an entity are 4) co___, v____, and ac___
A
1) substantive analytical procedures
2) support
3) records
4) complete, valid, and accurate
17
Q
Define Data Visualization
the 1) gra___ re___ of 2) in__ and d___
A
1) graphical representation
2) information and data
18
Q
SSBI software lets financial accountants perform 1) an____and create financial 2) d___ to support 3) d___n-m____
A
1) analytics
2) dashboards
3) decision-making
19
Q
Define Dashboard
graphical 1) us___ int____ that shows 2) k___ pe____ indicators for an organization
A
1) user interface
2) key performance
20
Q
This dashboard brings together analyses of different elements of the financial statements. Users can quickly see key performance indicators that provide insight into overall business performance.
The dashboard information can be viewed by year, quarter, or month using the tabs across the top.
- The dashboard information can be viewed by year, quarter, or month using the tabs across the top.
-The top row is a snapshot of how revenue, expenses, liabilities, assets, gross profit, and cash compare to goals.
-The visualizations in the dashboard provide an analysis of revenue and expenses, total assets and total liabilities, and a visualization that allows the user to choose an account to view compared to the prior year.
-The table in the top left of the dashboard provides the top expenses incurred by the company
A
21
Q
Frequently used in business, 1) da___ are a useful 1.1) to___ to 2) com____ key 3) in___ to everyone who 4) n___ it.
A
1) dashboards
1.1) tool
2) communicate
3) information
4) needs
22
Q
While financial accountants analyze financial statements for 1) ex___ reporting, managerial accountants deal with 2) in___ reporting and 3) pe___ analysis
A
1) external
2) internal
3) performance
23
Q
Analytics in Managerial Accounting
With SSBI software, management accountants can more easily use data to help 1) id___ and manage 2) r___, improve 3) bud___ and for___ (by using more ___ ), and automate 4) in___ reporting.
SSBI software can also help identify operational 5) im___ and create 6) da___ of 7) k___ pe____ in____ (KPI)
A
1) identify
2) risks
3) budgeting and forecasting (by using more data)
4) internal
5) improvements
6) dashboards
7) key performance indicators
24
Q
The top visualization in the dashboard is called a highlight table. The colors are on a scale from light to dark. Darker colors indicate higher sales and lighter colors indicate lower sales. User can quickly locate high performing and low performing products. For example, the darkest color is technology sales in 2021 in the month of November.
The bottom visualization in the dashboard provides both sales and profit margin information by product and subcategory. The colored dots represent individual sales to customers by total amount. The color of the dots indicates the profit ratio on each sale. The color scale of profit ratio ranges from negative 50 percent (dark red) and positive profit ratios up to 50 percent (dark black).
_______________________________________
This product dashboard provides management with 1) r__ ___me updates of sales and 2) p___ information, enabling management to identify and respond to possible 3) is___ quickly.
For example, customers with negative profit ratios can be investigated immediately.
A
1) real time
2) profit
3) issues
25
Analytics in Tax Accounting
Data analytics can analyze the tax efficiency of 1) bu___units, identify tax 2) op___, and aid in evaluating 3) g__ opportunities
1) business
2) opportunities
3) global
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Analytics in Tax Accounting
-Data analytics is used to help with tax 1) co___
-2) au___ of data gathering for tax compliance can help 3) sp__the process, leaving the tax accountant with more 4) t___ to do tax 5) an__ and p___g
-tax 6) da___s can help organizations monitor real time tax positions
1) compliance
2) automation
3) speed
4) time
5) analysis and planning
6) dashboards
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1.2 What are the Stages of the Data Analysis Process?
28
What are the 3 stages of the data analysis process?
1. P
2. A
3. R
1. Plan
2. Analyze
3. Report
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Data Analysis Process
Following a data analysis process helps 1) a___that data 2) an___ are performed 3) ef___ and e_____y.
1) assure
2) analyses
3) efficiently and effectively
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Data Analysis Process; Stage 1: Plan
this includes
-identifying the 1) m____ n for the analysis,
-determining the 2) o___ and 3) q____ to answer
-devising a 4) st___ to 5) p___ the analysis.
1) motivation
2) objective
3) questions
4) strategy
5) perform
31
What are the 3 parts for Stage 1: Plan (data analysis process)
-understand the 1) mo___: understand the 2) re___ for the data analysis
-determine the 3) ob___: articulate the 4) go___/obj___, and develop a 5) sp___ q___(s)
-6) d___ the data and analysis 7) st___: 8) i___ the necessary data and analysis 9) me___to answer 10) qu___
1) motivation
2) reason
3) objective
4) goal/objective
5) specific questions
6) design
7) strategy
8) identify
9) method
10) questions
32
Define Motivation
the 1) r___n or stimulus for 2) pe___g data analysis
1) reason
2) performing
33
Data Analysis Process; Stage 1: Plan Understand Motivation
it is 1) ___ we are doing the analysis. The “why” behind a project can vary from taking advantage of opportunities to solving problems, and its source can be 2) ex___l or i___
1) why
2) external or internal
34
Data Analysis Process; Stage 1: Plan Understand Motivation
External motivation: The project originates from a request or requirement by 1) a___ party, such as 2) ex___ sta_____s. These external stakeholders could be investors, creditors, supply chain partners, industry regulators, or government agencies. Another example of external motivation is when someone 3) int____ to the organization, but on a 4) d____t team, assigns the project.
Internal motivation: The project is motivated by a desire to 5) b___ serve a client, better 6) un____ phenomena to 7) ___ business intelligence, or to perform job 8) res____. Projects are motivated internally when the incremental information gained is believed to outweigh 9) po___ costs involved with performing the data analyses.
1) another
2) external stakeholders
3) internal
4) different
5) better
6) understand
7) gain
8) responsibilities
9) potential
35
Define Objective
the projects g___
goal
36
Data Analysis Process; Stage 1: Plan Determine the Objective
A clear objective 1) na___s the analysis’ 2) f___, and 3) s___ questions that guide the analysis can be developed based on it.
1) narrows
2) focus
3) specific
37
Data Analysis Process; Stage 1: Plan
Design the Data and Analysis Strategy
-Developing a strategy for the project is the final step in the planning stage
There are 2 aspects to this:
-determining the data necessary to 1) an__ q____
-deciding what 2) t___ of analysis is 3) ap___ considering both the data and those questions.
1) answer questions
2) type
38
Data Analysis Process; Stage 1: Plan
Design the Data and Analysis Strategy
Designing a strategy for the data involves identifying the 1) sp____ d___ needed and 2) kn____how to 3) ac___ it.
There are 2 categories of data. What are they ?
1) specific data
2) knowing
3) access
the 2 categories are internal and external data
39
Data Analysis Process; Stage 1: Plan
Design the Data and Analysis Strategy
Internal data are found 1) w____ the organization. This includes 2) tra___ data, gen___ le__ data, sa___ data, cus____ data, v____ data, internal do___, and internal e___
External data are acquired from 3) o___the organization. Data like this might come from 4) ____ media, we____, we____r data, go___ data, and m__s.
1) within
2) transaction data, general ledger data, sales data, customer data, vendor data, internal documents, and internal email.
3) outside
4) social media, websites, weather data, government data, and maps.
40
What are the 4 types of Data Analytics?
1. D
2. Di
3. Pr
4. Pr___e
1. Descriptive
2. Diagnostic
3. Predictive
4. Prescriptive
41
Out of the 4 types of Data Analytics, which is the most common and easily understood analytics?
Descriptive
42
Define Descriptive Analytics
designed to 1) un____d what is 2) cu___ happening or what has happened in the 3) p___
1) understand
2) currently
3) past
43
4 types of Data Analytics: Descriptive Analytics
They are the 1) ___ analytics performed to help understand 2) d____
3) S___, co___, av__, m___n, st___d dev___, and pr____ s are examples.
1) first
2) data
3) Sum, count, average, median, standard deviation, and proportions
44
Define Diagnostic Analytics
designed to understand 1) ___ something happened
1) why
45
4 types of Data Analytics: Diagnostic Analytics
The information gained from descriptive analytics about what happened lets us drill down further to understand 0) w___. The results of these analyses inform 1) d___n-m___ about actions in the 2) f___
Examples include 3) an__y and o___ detection, tr___ analysis, and p___n recognition.
0) why
1) decision-making
2) future
3) anomaly and outlier detection, trend analysis, and pattern recognition.
46
Define Predictive Analytics
helps understand what is likely to happen in the ____
future.
47
4 types of Data Analytics: Predictive Analytics
Predictive analytics use 1) d__a, st____l algorithms, and machine l____g to identify the likelihood of 2) f____ outcomes based on 3) hi____ data.
The goal is to use what is 4) k___n about the 5) p___ to make a 6) b____r assessment of what 7) m___ happen in the future.
8) For____, reg____ analysis, and ti__-s___ ies analysis are a few examples.
1) data, statistical algorithms, and machine learning
2) future
3) historical
4) known
5) past
6) better
7) might
8) Forecasting, regression analysis, and time-series analysis
48
Define Prescriptive Analytics
determines the 1) b___ co____ of action to achieve a 2) g___l in a 3) sp___ sc___
1) best source
2) goal
3) specific scenario
49
4 types of Data Analytics: Prescriptive Analytics
These analyses go beyond descriptive and predictive analyses by recommending 1) __ or m___ po____ courses of action.
Prescriptive analytics include 2) op____on and w___-___ analyses
1) one or more possible
2) optimization and what-if analyses
50
Data Analysis Process; Stage 2: Analyze
This stage includes data 1) pr___ , 2) bu____ inf___ m___, and 3) e___g the data
1) preparation
2) building information models
3) exploring the data
51
Data Analysis Process; Stage 2: Analyze
Prepare Data
Good quality data result in good quality analyses, so preparing the data for analysis is a critical step in this stage. This process is often referred to as e___ t-tr___m-l___ (ETL).
extract-transform-load (ETL).
52
Data Analysis Process; Stage 2: Analyze
Prepare Data
What are the 3 things to prepare data?
-E___
-Tr__
-Lo___
-Extracting
-Transform
-Loading
53
Data Analysis Process; Stage 2: Analyze
Prepare Data
-Extracting is the process by which data are 1) ret___ from a source. This could be downloading an Excel file or extracting data from a database or a data warehouse.
-Transforming the data occurs when data are 2) cl___, re___d, and/or int___d with other data prior to using it for analysis.
-Loading is the process of 3) imp___ transformed data into the 4) s____ u___ed to perform analyses. There are many types of analysis software available, including Excel, Power BI, and Tableau.
1) retrieved
2) cleaned, restructured, and/or integrated
3) importing
4) software used
54
Define Data Profiling
The first step is determining if data needs to be 1) c___. The process of 2) re___ the data for 3) pos___ is___ is called data profiling
1) cleaned
2) reviewing
3) possible issues
55
Data Analysis Process; Stage 2: Analyze
Prepare Data
To verify all the data have been extracted, you can compare the row counts of the data extracted to the total number of rows that should be in the data. To ensure that the data were transferred correctly, compare the amounts transferred to control amounts
56
Data Analysis Process; Stage 2: Analyze
Build Information Models
Information modeling is the creation of information needed for 1) an___ pur____, starting from the data 2) co___d.
Examples are calculations such as 3) ___t income, ___ margin, total a____ , or even br___ -even point in sales dollars.
1) analysis purposes
2) collected
3) net income, profit margin, total assets, or even break-even point in sales dollars.
57
Data Analysis Process; Stage 2: Analyze
Explore Data
The core goal of data analysis is to 1) e____ data to 2) id___ pat___, tre__, or u__ observations.
Exploring data lets us 3) di___r, qu___, and inv___ data relationships to successfully execute data analysis 4) obj____
1) explore
2) Identify patterns, trends, or unusual
3) discover, question, and investigate data relationships
4) objectives
58
Data Analysis Process; Stage 3: Report
The goal of this stage is to determine if the analyses 1) m___t the project’s 2) o____and then to 3) sh___ the results.
4) I____ the analyses and 5) com___ the results is a crucial stage–an amazing analysis that 6) d__ ___ meet the project’s objectives is 7) u____.
Moreover, if the results are not communicated effectively, then the analyses and recommendations 8) c___ be acted on.
1) met
2) objectives
3) share
4) interpreting
5) communicating
6) does not
7) useless
8) cannot
59
Data Analysis Process; Stage 3: Report
Interpret Results
Data analysis interpretation is the process of 1) re___ analyses to be sure they make 2) s___ based on the project’s 3) o__ and that the results are 4) va___ and re___
Does the analysis 5) m___ the objective?
1) reviewing
2) sense
3) objective
4) valid and reliable
5) meet
60
Data Analysis Process; Stage 3: Report
Communicate Results
The results of a data analysis project can be communicated 1) o___, with vis___ or in w___.
Typically, data analysis communication will include data 2) vi__
1) orally, with visuals, or in writing.
2) visualizations
61
What's the acronym to remember the Data Analysis Process?
MOSAIC
Motivation
Objective
Strategy
Analysis
Interpret
Communicate
MOS - Stage 1: Plan
A - Stage 2: Analyze
IC - Stage 3: Report
62
1.3 What is a Data Analytics Mindset?
63
Define Data Analytics Mindset
the 1) pr____ h___ of 2) cri___ th___ through the 3) pl___ an___, and r__ng of data analysis results 4) ____ making and communicating a professional 5) c___ or d__
1) professional habit
2) critically thinking
3) planning, analysis, and reporting
4) before
5) choice or decision
64
Individuals with a data analytics mindset are 1) in____.
They always ask 2) “____” when interpreting 3) r____, they are 4) o__to learning new 5). te____, and they evaluate their own 6) th____.
How can you develop a data analytics mindset? Focus on developing 7) __ such as critical thinking, data literacy, technological agility, and communication skills.
1) inquisitive
2) why
3) results
4) open
5) technologies
6) thinking
7) skills
65
What are 4 skills you need to have a Data Analytics Mindset?
1. C____ T____
2. D___ Li___
3. T_____l Agility
4. Co____ skills
1. Critical Thinking
2. Data. Literacy
3. Technological Agility
4. Communication skills
66
Define Critical Thinking
1) di___ re____ used to 2) in_____ un____, and e____e an event, op____, or an i___
1) disciplined reasoning
2) investigate, understand, and evaluate an event, opportunity, or an issue
67
Define Reasoning
the 1) ____ process of 2) l____forming 3) c____s, ju____, or in____ from facts.
1) human
2) logically
3) conclusions, judgments, or inferences
68
Critical Thinking
Not only do employers want critical thinkers, but professional certification exams such as the CPA exam and the CMA exam also include assessment questions that test critical thinking skills.
Critical thinking is the 1) ___ of a data analytics mindset and should be integrated throughout the data analysis process
1) foundation
69
Define Data Literacy
ability to 2) u___ and co___ data
2) understand and communicate
70
Define Technological Agility
An 1) a____ of the latest 2) tec___ dev___ and a 3) w____ to work with new 4) ___ls
1) awareness
3) technological
3) willingness
4) tools
71
Technology Skills
We can become technologically agile by learning new technology and developing the skills that help us to do so.
In fact, being comfortable learning new technology leads to more agility. This “learn to learn” mindset is what employers are looking for in new employees.
72
1.4 How is a Data Analytics Mindset Applied?
73
What are the 6 elements of critical thinking?
1. S___
2. P____e
3. Alt____s
4. Ri___
5. Kno___
6. Se___-ref____
What's the acronym ?
1. Stakeholders
2. Purpose
3. Alternatives
4. Risks
5. Knowledge
6. Self-reflection
SPARKS
74
The 6 elements of critical thinking
Keep in mind that these elements are not sequential, rather they are 1) re____
In other words, the order in which you consider the elements is 2) ___ as important as 3) co___ t___ through them
1) recursive
2) not as
3) continually thinking
75
The 6 elements of critical thinking: Understand the Stakeholders
Define Stakeholders
individuals or groups with an 1) i____ in the outcome of a data analysis project
Stakeholders can be
2) ___ or ____. to an organization
1) interest
2) internal or external
76
Define internal stakeholders
individuals or groups involved in a 1) b___ operations. They include an organization’s 2) ____s and em___
1) businesses
2) managers and employees
77
Define external stakeholders
individuals or groups 1) ___ the company.
Examples include investors and creditors, regulators, organizational partners (clients or customers, suppliers, outsource partners, and donors), and community leaders and members
1) outside
78
The 6 elements of critical thinking: Understand the Stakeholders
Overall, understanding the stakeholders helps us to better 1) un___ the 2) i____ of the analysis and can 3) g___ our choice of 4) d___ and analysis 5) m___.
1) understand
2) impact
3) guide
4) data
5) methods
79
The 6 elements of critical thinking: Identify the Purpose
Knowing the reason for data analyses and articulating specific questions maintains 1) f___ on the data and analyses steps that will achieve 2) o___
The importance of identifying specific questions was covered with the discussion of data analysis objectives. Here, the emphasis is on repeatedly returning to those questions to keep the analysis on 3) ___
1) focus
2) objectives
3) track
80
The 6 elements of critical thinking: Consider Alternatives
Performing data analyses involves many choices–which questions to evaluate, what data are needed, which method to use, and how to best communicate the results. How should we consider these alternatives?
First, 1) id___y the available 2) c___, rank them, then choose the 3) h___ ranked option.
As with all business decisions, weighing the 4) c___ of performing the analysis against its expected 5) be___ is good practice.
While we should only perform analyses where the 6) b___ exceed the cost, the costs and benefits of performing an analysis 7). c___ always be quantified. In these cases, think critically about the 8) ch___s and select the option that 9) __t supports the purpose.
1) identify
2) choice
3) highest
4) cost
5) benefits
6) benefits
7) cannot
8) choices
9) best
81
The 6 elements of critical thinking: Consider Alternatives
To select the best data for the analysis, 1) ra___ the data by their 2) r____ and availability.
Data that are both relevant and available will rank 3) hi____ than data that are relevant but 4) ___t available or data that are 5) ir__
1) rank
2) relevance
3) higher
4) not
5) irrelvant
82
The 6 elements of critical thinking: Consider Alternatives
The methods of analysis that are most relevant for this question are 1) d____e and d____ methods.
1) descriptive and diagnostic
83
The 6 elements of critical thinking: Assess Risks
There are many risks to consider when performing data analyses, and it’s important to examine 1) a__ as____ of the analysis to identify them. This begins with the data and extends to 2) p___l bi___s, including our own, that may be held by the stakeholders
1) all aspects
2) potential biases
84
What are the 4 types of risks?
1. D___
2. A___
3. As___
4. B__
1. Data
2. Analysis
3. Assumptions
4. Biases
85
Ch 2 (2.1-2.3)
86
Define BIT
b___ digit (___ or __)
-l____t level
binary digit (0 or 1)
-lowest level
87
Define byte
___ ___ together
-____ character
8 BITS together
-one character
88
Define attribute
(or 1) f___) – a meaningful group of 2) ch___
1) field
2) characters
89
Define Tuple (or r___)
a meaningful group of a___
record
a meaningful group of attributes
90
Define Database
a meaningful group of t___
tables
91
2.1 How Does Understanding Data Storage Help Answer Questions?
92
Define Relational Databases
A collection of 1) lo___y related data that can be 2) re___, ma___d, and up__d to meet users’ 3) n__
Data, regardless. of type/format needs to be 4) s___ somewhere.
1) logically
2) retrieved, manipulated, and updated
3) needs
4) stored
93
Define table
How data related to an object of 1) in___t are stored in a 2) re___al database.
also called a 3) f___, meaningful group of 4) r___
1) interest
2) relational
3) file
4) records
94
Tables are compromised of rows and columns
rows: each row represents one 1) re___ or in___ of the table's 2) o___
columns: they reflect the 3) at____, which are the data 4) f___s that describe 5) dif___t a___s of the records
1) record or instance
2) object
3) attributes
4) different aspects
95
What are the 3 Databases Elements ?
1. Re___s
2. Ev___
3. Ag___
1. Resources
2. Events
3. Agents
96
3 Databases Elements: Define Resources
1) Ide___ objects that have economic 2 ) v___ to the business entity
What would be an example?
3) -in___ items
What would be attribute examples?
4) -co__
-4) de____
1) identifiable
2) value
3) inventory
4) cost and description
97
3 Databases Elements: Define Events
An organization’s business 1) a___
What would be an example?
2) -___ order
What would be attribute examples?
3) -s___ order number
-d___ of sales order
1) activities
2) order
3) sales and date of sales order
98
3 Databases Elements: Define Agents
Represent 1) pe__e or org___s about which data are 2) c___d.
What would be an example?
3) -em___
What would be attribute examples?
4) -n__e
-ad__
1) people or organizations
2) collected
3) collected
4) name and address
99
You have an extract of the payroll data for the last fiscal year. Payroll runs twice a month. The spreadsheet has the following columns: Pay Date, Employee, Department, and Payment Amount.
How would you determine the total number of employees by department?
a) Set Department as rows and set Count of Employee as values.
b) Set Employee as rows and set Department as columns.
c) Set Department as rows and set Sum of Employee as values.
d) Set Department as rows and set Count of Employee as columns.
a
100
You have an extract of the payroll data for the last fiscal year. Payroll runs twice a month. The spreadsheet has the following columns: Pay Date, Employee, Department, and Payment Amount.
How do you summarize the data as a pivot table to show the total payroll payments by department?
a) Set Department as columns and set Sum of Payment Amount as measures.
b) Set Department as rows and set Sum of Payment Amount as values.
c) Set Department as rows and set Payment Amount as columns.
d) Set Department as dimensions and set Sum of Payment Amount as values.
b
101
There is a symbol for a key next to the AssetTagID attribute in the first table and the CategoryID in the second table. This symbol identifies the primary key
Define Primary Key
A 1) un___ v__ for each data 2) r__ in a database table
1) unique value
2) row
102
Define foreign key
A 1) co___ in a table that is a 2) pri___ k___ in another table.
1) column
2) primary key
103
Linking tables creates a relationship that makes it possible to pull information from both tables and create calculations of depreciation for every asset in the asset data table.
If tables are not linked, the information 1) c__ be retrieved for more than one table in a way that
1) cannot
104
Define Query
A request for data from a database so the data can be 1) re___ or ma___d
1) retrieved or manipulated
105
Query
It provides the computer instructions for 1) j___g, ad___, up__, de__, retrieving, or man____ the data in its tables.
Queries can be 2) cr___ and u__ once or 3) st___ for later reuse.
1) joining, adding, updating, deleting, retrieving, or manipulating
2) created and used
3) stored
106
Define Structured Query Language (SQL)
The standard query 1) co____ lan___e for database management
also called __
1) command language
also called sequel
107
Define Join
The process of combining 1) r__ from two or more 2) t___based on a 3) re___d co___ between them
1) rows
2) tables
3) related column
108
What are the 4 types of joins?
Inner
Left
Right
Full
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Define Inner join
-selects all 1) r___s from 2) b__. tables with 3) m____ values
-the results will 3) __t have 4) n___ values in any key column
1) rows
2) both
3) matching
4) not
5) null
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Define Left join
-returns 0) __ records from the 1) ___t table and the 2) m__records from the 3) r__table
-there could be 4) n___ values if there’s 5) __o matching value in the right table to a left table record
0) all
1) left
2) matching
3) right
4) null
5) no
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Define Right join
-returns all the records from the 1) r__ table and the matched records from the 2) l__ table
-could return 3)__l values if there’s 4) _t a matching value in the left side to the record in the right table
1) right
2) left
3) null
4) not
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Define Full join
-returns all records when there’s a match in either 1) ___ or ___
-nulls could be present in this result if there are 2) n__ m____g records between the tables
1) left or right
2) no matching
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2.2 How Do Spreadsheet Functions Analyze Large Amounts of Data?
114
Frequently used calculations are often built into analysis software as 1) fu____,
Define Functions
2) pre___ fo___s that perform 3) ca___s
1) functions
2) predefined formulas
2) calculations
115
Define Dimensions
variables used to 1) d__l d___n or di___te analysis measures
1) drill down or disaggregate
116
2.3 How Do We Organize Data Sets for Analysis?
117
Define Data Organization
the process of 1) re____ data to make it 2) e____r to u____
1) rearranging
2) easier to understand
118
Define Pivot Table
An analysis tool that 1) su___s and re____selected 2) co____ and r___ of data in a spreadsheet, database, or business intelligence
1) summarizes and reorganizes
2) columns and rows
119
Both powerful and easy to use, a 1) p____ ta__ is also one of the most common tools you will use in your accounting career
1) pivot table
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What are the 5 main components of a pivot table?
1. F__
2. Co____
3. R__s
4. V___
5. F____
1. Fields
2. Columns
3. Rows
4. Values
5. Filters
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Define Fields
The data 1) el__ navailable for use in the pivot table.
1) elements
122
Define Columns
When a field is chosen for a column area, only the 1) un___ v__s of the field are listed across the 2) t_
1) unique values
2) top
123
Define Values
Each value is kept in a pivot table 1) c__ and displays the 2) su____ in___n.
Examples are sum, average, or count
1) cell
2) summarized information
124
Define Filters
apply 1) re___ to the entire table
1) restriction
125
A Pivot Table displays sales by product type, year of sale, and the total dollar amount of sale. You would like to only see three of the 15 specific product types. The best way to focus only on the specific product types you are interested in is to use
a) a filter
b) cut and pate
c) the SORT function
d) the SUMIG function
a) filter
126
Simultaneously filtering for multiple dimensions is often referred to as slicing (or 1) ___ and ___)
Define Slicing
The process of 2) b__ data down into 3) __er parts
1) slice and dice
2) breaking
3) smaller
127
Define Slicers
analysis tool that 1) s____e the resulting analysis measures per the selected 2) dim__
1) seperate
2) dimensions
128
You have an extract of the sales data of the last three fiscal years. The extract is a spreadsheet with the following columns: Sales Date, Sales Order ID, Sales Amount, Product, and Sales Region. How would you determine the average sales transaction amount?
a) Keep rows and columns as empty and set Average of Sales Amount as values.
b) Set Sum of Sales Amount and Count of Sales Order ID as values.
c) Set Sales Order ID as columns and set Average of Sales Amount as values.
d) Set Sales Order ID as rows and set Average of Sales Amount as values.
-it's not c or d but the book didn't give me the answer. So we will say A
129
2.4 Which Descriptive Measures Help Us Understand Data?
130
Define Measure of Location
determine the 1) a___,or t___al, ob___ in the data set
1) average, or typical, observation
131
Define Measure of Central Tendency
a 1) si___value that describes a set of data by 2) id___ the 3) c___ po___n within that data set
1) single
2) identifying
3) central position
132
Measure of Central Tendency
What are the 3 measures of central tendency?
mean
median
mode
133
Determining the 1) m__ and m___ is the first step for understanding data during descriptive analysis
1) mean and median
134
-Mean: sum of all observations in a dataset divided by the total number of observations
-affected by 1) o__s
-Median: the middle value when the data is arranged from smallest to largest
-2) n__t af___ as much by outliers (if there outliers, 3) m__ is a better representation of the central value)
-Mode: observation that occurs most frequently | useful in data sets with small number of unique values
1) outliers
2) not affected
3) median
135
Define measures of dispersion
Measures that describe the amount of 1) va___ in the data to help us understand what causes that 2) di___
-are the data spread out or compact
-how far apart are the data points from the mean?
1) variation
2) disparity
136
Tools and Knowledge
-1) un___ how the m__s are calculated
-2) k___ how to in__t results
1) understand how the measures are calculated
2) knowing how to interpret results
137
There are two widely‐used measures of dispersion:
1. V___
2. S___d D___
1. Variance
2. Standard Deviation
138
Define Variance
A measure of 1) di___ that finds the 2) av___ squared distance between the data 3) p___ in the data 4) s_t and the mean
1) dispersion
2) average
3) points
4) set
139
Define standard deviation
A statistic that measures the dispersion of a data set relative to the mean. It is the 1) s___ r__ of the variance
this is usually reported it’s 2) e__ to interpret because it’s in the same units as the mean
1) square root
2) easier
140
A low standard deviation indicates the observations in the data set tend to be close to the mean of the data set.
A high standard deviation indicates the values are spread out over a wider range
141
Define Measures of Shape
Measures that 1) d___e the 2) di___ of the data in a data set.
-can reveal the 3) b__ m____e of the 4) central tendency to 5) u__/sh__ pat__ in the data
1) describe
2) distribution
3) best measure
4) central
5) use/show patterns
142
Data sets are either 1) sym____ or a___al in shape
In a symmetrical distribution, the mean, median, and mode are 2) ___l and the data distribution to the right of the mean mirrors the data to the left of the mean.
A symmetrical distribution will look like a 3) b__ c___ in a graph
1) symmetrical or asymmetrical
2) equal
3) bell curve
143
What are the 2 measures of shape ?
-s___ss
-ku___
-skewness
-kurtosis
144
In a symmetrical distribution, what conclusion can be made about the mean, median, mode?
The mean, median, mode, will have the ___ values
same
145
Define skewness
the 1) l__ of sy___y of data
1) lack of symmetry
146
Skewness
Distributions that tail off to the right of the mean are considered 1) p__ skewed
1) positively
147
Define Skewness
Distributions that tail to the left of the mean are 1) ne___ skewed
1) negatively
148
Define Kurtosis
how 1) p___d or f__t a his___ of the data is
1) peaked or flat a histogram
149
The coefficient of kurtosis measures measures degree of the kurtosis of a distribution
If the CK is greater than 0) t__e, then the data are somewhat 1) p___ with l__ dispersion.
If the CK is less than three, the data are somewhat 2.0) fl__ with a 2) w__ degree of dispersion
0) three
1) peaked with less
2) wide degree of dispersion
2.0) flat
150
The shape of a distribution can be visualized with two other measures:
-fr___ distribution
-hi__
-frequency distribution
-histogram
151
Define Correlation analysis
reveal 1) re___s in data by 2) m___g the 3) li___ relationship between 4) t___ variables.
-The first step is understanding how variables are 5) co__
-The second step involves 6) ca___ the correlation.
1) relationships
2) measuring
3) linear
4) two
5) correlated
6) calculating
152
Define correlation coefficient |of contunous varables
Also known as the 1) P____n pro__t-mo___ correlation coefficient, it is a numerical value between 2) ___ and __ that measures the 3) linear relationship of 4) c__s variables
the higher the absolute number, the 5) gr__ the st__h of the relationship between the variables
1) Pearson product-moment
2) −1 and +1
3) linear
4) continuous
5) greater the strength
153
A correlation can be n___, p___e, or __ro
negative, positive, or zero
154
A negative correlation is an 1) i___relationship.
As one variable increases, the other 2) d___s.
There is a negative relationship between soup sales and temperature because as temperatures decrease, the soup sales increase
1) inverse
2) decreases
155
No correlation indicates no 1) re____ between the variables.
We would not expect the outdoor temperature to have an impact on the sale of cereal, for example
1) relationship
156
A positive correlation coefficient indicates that as one variable 1) in___s, so 2) d__ the o___r variable.
We would expect a positive relationship between ice cream sales and outdoor temperature. As the temperature rises, ice cream sales tend to rise as well
1)increases
2) does the other
157
We can also consider the 1) st__ of a relationship.
The higher the correlation coefficient, between a negative 1 and a positive 1, the 2) s___r the correlation
1) strength
2) stronger
158
2.5 How is Visualization Used in Data Analysis?
159
What are the 2 types of data visualization ?
-E ______ data visualization
-E ______ data visualization
-Exploratory data visualization
-Explanatory data visualization
160
Define Exploratory data visualization
uses data visualization tools and techniques to explore data to find 1) in___
Exploratory data visualization helps 2) u____d the data and identify underlying 3) p___ns, tr___s, or an___s.
1) insights
2) understand
3) patterns, trends, or anomalies
161
Define Explanatory Data Visualization
uses data visualization tools and techniques to 1) co___ate the re___ of an analysis.
It is used to 2) e___ the results of an analysis, 3) ___ow rel____ in the data, and 4) co___e insights.
1) communicate the results
2) explain
3) show relationships
4) communicate
162
Visualization is powerful because it can 1) q___ and e___ly r__al ins___ buried in raw data.
1) quickly and efficiently reveal insights
163
Define categorial data
1) la___or na___ data that can be sorted into 2) g___ps according to specific 3) ch____
1) labeled or named
2) groups
3) characteristics
164
Data from the following 4 types of measurement scales can be used for visualizations
-categorical (nominal) – data can only be categorized
-ordinal – data can be categorized and ranked
-interval: numbers and have a definite interval in them (ex tempature) cate, ranked, and evenly spaced
-ratio (quantitative) data: meaningful useful zero (ex weight, sport scores)
165
3.1 How Does Motivation Inform Objective‐Based Data Analysis Questions?
166
Understanding the motivation to perform an analysis and identifying its objective also helps create specific, objective‐based questions.
After all, it is impossible to get the right answers if we do not know what to ask.
167
Define motivation
data analytics in accounting is the 1) r__ the analysis is being 2) p__
1) reason
2) performed
168
What are the 4 four forces of motivation?
1. O
2. Pr__ i___
3. Pro___ sol__
4. Process and p____
1. Opportunity
2. Professional Issues
3. Problem Solving
4. Process and Performance Assessment
169
Determine the Objective
The objective of a data analysis project naturally follows the motivation. Let’s go back to that common motivation for data analysis, an underperforming business unit:
-The motivation is to solve a 1) pr__m by evaluating the unit’s performance to discover 2) w__ it is underperforming.
-It's necessary to be more 3) sp__ because poor performance could have several 4) ca__
-The first step is to 5) sp__ the areas of performance to 6) inv___e and articulate what those investigations should accomplish.
In other words, it is important to 7) cl__y the g__ of the data analysis.
1) problem
2) why
3) specific
4) causses
5) specify
6) investigate
7) clarify the goal
170
Study the flowchart for developing data analysis questions
171
Start: Does the question address the objective?
Yes - then move to "does the question a__ o__ to__c?"
No - r___ the question to address the ob__ of the analysis
Yes - then move to "does the question address one topic?"
No - revise the question to address the objective of the analysis
172
Does the question address one topic?
Yes - is the question me___
No - br__ the question down into ___b-questions
Yes - is the question measurable
No - break the question down into sub-questions
173
Is the question measurable?
Yes - can we ob___ the data needed to answer the question?
-then k__ the question
No - can the question be ch__ to be m__e?
Yes - can we obtain the data needed to answer the question?
-then keep question
No - can the question be changed to be measurable?
174
Can the question be changed to be measurable?
No - ___ the question
No - drop the. question
175
Role of critical thinking
-1) m__, ob___s, and q__s need to be critically evaluated
1) motivation, objectives, and question
176
What are the critical thinking elements?
S
P
A
R
K
S
Shareholders
Purpose
Alternatives
Risks
Knowledge
Self-reflection
177
Critical thinking elements: Shareholders
1) con___ the perspectives of stakeholders helps 2) id__y the obj___e and 3) de___ g__d questions
1) considering
2) identify the objective
3) develop good
178
Critical thinking elements: Purpose
critically thinking through the purpose of data analyses is the 1) li__ between a define 2) ob__ and sp__ questions
-the questions will be different depending whether the purpose is to describe and diagnose 3) cur___conditions or predict and prescribe 4) f___ outcomes
1) link
2) objective and specific
3) current
4) future
179
Critical thinking elements: Alternatives
evaluating different 1) me__of analysis 2) in___ the likelihood of selecting the 3) b__ op_ for the project’s purpose
1) methods
2) increases
3) best option
180
Critical thinking elements: Risk
being aware of potential risks makes it possible to also 1) mi__ them when evaluating 2) mot___, ob___s, and qu__
1) mitigate
2) motivation, objectives, and questions
181
Critical thinking elements: Knowledge
successfully completing a project requires 1) co__g we have the necessary 2) k)) to do so or doing additional 3) res___ to obtain that knowledge
1) confirming
2) knowledge
3) research
182
Critical thinking elements: Self-reflection:
understanding the purpose of the analysis makes it easier to apply the experience of performing it to future data analytics contexts and tasks
-why are we really doing this
183
3.2 What are Descriptive Objectives?
184
Descriptive questions are often the 1) f__t asked in any analysis because 2) u___g the data is necessary before beginning more advanced analyses.
1) first
2) understanding
185
Descriptive Questions
designed to 1) b__understand data to answer business 2) qu__
To develop good descriptive questions, first identify the 3) ob__ of the analysis, then 4) b__ that down into questions.
Remember, a good question is one that relates to the 5) ob__ is sp__c, m__e, and can be answered with the available data
1) better
2) questions
3) objective
4) break
5) objective, is specific, measurable
186
Define Descriptive Questions
Analysis questions designed to 1) u___nd something that is 2) c___ happening or that has 3) h__d in the 4) p___
1) understand
2) currently
3) happened
4) past
187
Analyses commonly used to answer descriptive questions include measures of 1) fre__ lo__, di___n, and pe__
1) frequency, location, dispersion, and percentages
188
Frequency measures help us understand 1) ca___ of data.
Measures of location (mean, median, mode) reveal 2) a__e ob__ns in a data set.
Measures of dispersion (minimum, maximum, range, variance, and standard deviation) show how much 3) va___ there is 4) am__ the observations in the data set.
Measures of percentage change 5) co___e results to 6) p__r periods and the percent of 7) to__
1) categories
2) average observations
3) variance
4) among
5) compare
6) prior
7) total
189
3.3 What are Diagnostic Objectives?
190
Diagnostic questions build on 1) de__ analyses and further 2) ex__ the data to find the 3) ou__cause.
Diagnostic analytics do this by looking for 4) a__s, cor___s, p__ns, or tr__
1) descriptive
2) explore
3) outcome’s
4) anomalies, correlations, patterns, or trends
191
Define Diagnostic Questions
identify a 1) pr___ or is__ to understand 2) w__ an 3) ou__ occurred.
1) problem or issue
2) why
3) outcome
192
There are four common types of diagnostic analyses:
-an__ detection
-cor__
-pa__ detection
-t__ analysis
-anomaly detection
-correlation
-pattern detection
-trend analysis
193
3.4 What are Predictive Objectives?
194
Define predictive questions
Analysis questions designed to help understand what is 1) li___ to happen in the 2) f___
1) likely
2) future
195
In the same way, predictive analytics use 1) p___ and p___ data to create models so businesses can make predictions.
1) past and present
196
Predictive questions should be related to the 1) ob___, sp___ic, m___able, and the 2) app___ data and a___cs should be used to answer them.
1) objective, specific, measurable
2) appropriate data and analytics,
197
What are two common analyses that answer predictive questions ?
Tre___and regression analysis
Trendlines and regression analysis
198
Trendlines show the underlying functional relationship of data:
A 1) fun___ relationship is the effect of an 2) i____ent variable on a 3) d_____ variable.
A 4) li__function shows steady 5) incr___ or d___es over the range of the 6) in___t variable
1) functional
2) independent
3) dependent
4) linear
5) increases or decreases
6) independent
199
Define linear regression
A tool for building mathematical and statistical models to explain the relationship between a 1) de___ variable and one or more 2) in___nt variables
1) dependent
2) independent
200
Predictive analytics build models to 1) pr___ or b___r understand a phenomenon.
1) predict or better
201
A variable is a 1) d__ field used for 2) an__is.
A dependent variable is the outcome 3) m__
-this is what your trying to ___
-___ side of equation (Y)
Independent variables are the variables that 4) in____e the 5) de___ variable
-trying to predict the ___ variables
1) data
2) analysis
3) measure
-predict
-left
4) influence
5) dependent
-dependent
202
Simple linear regression involves a 1) s__independent variable, while multiple regression involves 2) t___or m____ independent variables.
The goal of a regression model is finding the equation of the line that 3) b___t f__ the data.
1) single
2) two or more
3) best fits
203
Use of predictive analysis in accounting
-financial accountants: identify trends in 1) s__ or ex___
-cost accountants: 1) p__ co__, create fo__, and evaluate cost d__
-auditors: identify potential 3) ma___l m__ents
-tax accountants: for 4) t__ planning
1) sales or expenses
2) predict costs, create forecasts, and evaluate cost drivers
3) material misstatements
4) tax
204
Define multiple R:
Also called the 1) co__n co__, it measures the 2) st__th of the relationship between the 3) de__t and ind__nt variables.
It is a measure from 4) −__ to __
A positive number equals a positive correlation, so the variables move in the 5) s__ direction.
A negative number equals a negative correlation, where the variables move in 6) op__ directions.
1) correlation coefficient
2) strength
3) dependent and independent
4) −1 to 1
5) same
6) opposite
205
Define R Square (R^2)
Also called the coefficient of 1) det__, it is a measure of how 2) w__ the 3) re__on line f__ the data.
R2 gives the proportion of the variation in the 4) d__t variable that is explained by the 5) in__ variables.
The closer the R2 is to 6) __, the 7) b__ the regression line fits to the data
1) determination
2) well
3) regression line fit
4) dependent
5) independent
6) 1
7) better
206
Define Adjusted R^2
1) E__ how 2) w__l the regression 3) l__ fi__ the data.
4) Modifies the value of 5) R2 by incorporating the 6) sa__si__ and the number of 7) in__ variables.
Generally used to evaluate a multiple regression model.
The closer the adjusted R2 is to 8) __, the 9) b__the fit of the regression line to the data.
1) Explains
2) well
3) line fits
4) Modifies
5) R2
6) sample size
7) independent
8) 1
9) better
207
3.5 What are Prescriptive Objectives?
208
Define prescriptive questions
Prescriptive objectives build on 1) de___ of the 2) p___nt and predictions about the 3) fu__ to determine the 4) b__action.
Prescriptive questions investigate how to take 5) ad___of fu___e op___es or mi___ a future 6) r___outcome.
The analyses 7) sp__ the actions necessary to achieve the 8) d___ outcomes
1) descriptions
2) present and predictions
3) future to determine
4) bestt
5) advantage of future opportunities or mitigate
6) risk
7) specify
8) desired
209
The two most common methods of analysis used to answer prescriptive questions are 1) op___ models and 2) w__t‐___ analyses
1) optimization
2) what‐if
210
Define Optimization
is the process of selecting 1) va___ of va___ that 2) m__e or ma__ some quantity of 3) in__
Optimization modeling helps managers allocate 4) re___ more 5) e___y and make 6) c__t/p__ decisions.
1) values of variables
2) minimize or maximize
3) interest
4) resources
5) efficiently
6) cost/profit
211
The most common optimization model used in accounting is 1) l___ optimization.
1) linear
212
In linear optimization, the model is comprised of:
-D___ variables
-O___e function
-Co__
-Decision variables
-Objective function
-Constraints
213
Define decision variables
The 1) u__ va__ the model seeks to determine
1) unknown values
214
Define Objective function
The mathematical equation that describes the 1) o_ ta__t to m___ or ma__
1) output target to minimize or maximize.
215
Define Constraints
The 1) lim___, re___ts, or other re____ that must be imposed on any solution, such as 2) de__, m___l, or la__ constraints.
1) limitations, requirements, or other restriction
2) demand, material, or labor
216
The output from a linear optimization model will show the 1) op__ so__.
1) optimal solution
217
3.6 What are Data Analytics Motivations and Objectives in Professional Practice?
