Chapter 1
What is a dashboard?
a graphical user interface that shows key performance indicators for an organization
What are examples of diagnostic analytics?
anomaly and outlier detection, trend analysis, and pattern recognition
How has analytics in the audit profession grown?
audits have expanded beyond sample-based testing to include analyses of entire populations of audit-relevant data; auditors can review entire data sets to identify all exceptions, anomalies, and outliers; data driven audits reduce the time the client spends gathering information for the auditor and allows more time for the analysis, making audits a better experience for everyone involved
What does focusing on the purpose of the analysis do?
avoids wasting time on irrelevant findings
What does understanding the stakeholders help us do?
better understand the impact of the analysis and can guide our choice of data and analysis methods
What is the foundation of a data analytics mindset and should be integrated throughout the data analysis process?
critical thinking
What is the most common and easily understood analytics?
descriptive analytics (also performed first to help understand the data)
What are the two aspects to the developing a strategy stage?
determining the data necessary to answer questions and deciding what type of analysis is appropriate considering both the data and those questions
What is critical thinking?
disciplined reasoning used to investigate, understand, and evaluate an event, opportunity, or an issue
What does exploring data let us do?
discover, question, and investigate data relationships to successfully execute data analysis objectives
Why should data and analytics be thought as separately?
each is its own element; includes identifying both the data necessary for analysis and the appropriate analysis method
What is self-service business intelligence (SSBI) software?
easy-to-use, accessible software that can prepare data, analyze data, and report results
What is the alternatives element?
every choice should be the best option available; generating and ranking alternatives helps us make good choices
What do financial accountants analyze?
financial statements for external reporting
How can a data analytics mindset be developed?
focus on developing skills such as critical thinking, data literacy, technological agility, and communication skills
What are examples of predictive analytics?
forecasting, regression analysis, and time-series analysis
What is predictive data analytics?
forecasts what might happen in the future (what will sales be next year if we increase market share by 10%)
What is internal data?
found within the organization; includes transaction data, general ledger data, sales data, customer data, vendor data, internal documents, and internal email
What is prescriptive data analytics?
helps understand what should happen to meet goals and objectives (what is the most cost-effective way to ship our products)
What is diagnostic data analytics?
helps understand why something happened (why did sales decrease in region 1 in the prior year)
How should alternatives be considered?
idenitfy the available choices, rank them, then choose the highest ranked option
What does designing a strategy for the data involve?
identifying the specific data needed and knowing how to acces it
What is biases risk?
mental shortcuts that can affect decisions (do we have biases that could influence the data analysis; for example, assumptions about the cause of the sales decline could bias the preparation for the analysis or interpretation of the results)
What do prescriptive analytics include?
optimization and what-if analyses
What is the stakeholders element?
parties impacted by the data analysis; the potential impacts guide analysis and communication choices
What is data visualization used for?
perform data analysis and to communicate the results of data analysis
What are the three equally important stages in the data analysis process?
plan, analyze, and report
What does Alteryx let users do?
quickly design workflows that access, manipulate, amalyze, and output data; user-friendly and does not require knowing how to program
What is data?
raw figures and facts
What does the CPA evolution do?
recognize the rapidly changing skills and competencies the practice of accounting requires today and will require in the future
What are examples of descriptive data analytics?
sum, count, average, median, standard deviation, and proportions
What helps convert data to information?
technology
What section was added by the IMA to the CMA exam?
technology and analytics (make the exam more relevant to the current job market)
What does a data analysis process help assure?
that data analyses are performed efficiently and effectively
Who launched the CPA evolution in 2021?
the AICPA and the NASBA
What is data literacy?
the ability to understand and communicate data
What is information modeling?
the creation of information needed for analysis purposes, starting from the data collected
What has impacted how accountants, from auditors to financial accountants, do their jobs every day?
the growing availability of data, the techniques and tools used to create value from them, and the ease with which these tools can be used
What is ETL?
the process of retrieving raw data from a source, cleaning, restructuring, and/or integrating them with other data, and then loading the data into software for analysis purposes
What is data analysis interpretation?
the process of reviewing analyses to be sure they make sense based on the project's objective and that the results are valid and reliable
What is data profiling?
the process of reviewing the data for possible issues
What is a data analytics mindset?
the professional habit of critically thinking through the planning, analysis, and reporting of data analysis results before making and communicating a professional choice or decision
What is motivation?
the reason the analysis is being performed; why we are doing the analysis
What does the mnenomic SPARKS represent?
the six elements of critical thinking
What do the CPA and CMA exams now include?
the topic of data analytics
What is the goal of predictive analytics?
use what is known about the past to make a better assessment of what might happen in the future
What are examples of SSBI tools?
Alteryx, Microsoft Excel, Power BI, and Tableau
What can be used to remember the data analysis process?
MOSAIC
What does SSBI software let financial accountants perform?
analytics and create financial dashboards to support decision-making
What does new, user-friendly technology allow accountants to complete?
accounting functions, such as creating journal entries and preparing financial statements and reports, in a fraction of the time they used to take
What is exteral data?
acquired from outside the organization; data like this might come from social media, websites, weather data, government data, and maps
What can accountants focus on because repetitive accounting functions can be automated?
activities that add value to their organizations, such as evaluating controls, providing financial insights, and performing analyses to aid in business decision-making
What must accountants of the future be?
agile, creative, data and technology literate professionals
What areas of accounting are changes in data and technology impacting in the role of accounting?
all areas
What is technological agility?
an awareness of the latest technological developments and a willingness to try new things
What is a null value?
an unknown or missing value in a data set
What do accountants need to do?
be critically thinking problem-solvers who can use technology and data to drive business understanding and change; "think outside the box" to create value using data and analyses
How can one become technologically agile?
by learning new technology and developing the skills that help us to do so
What is analysis risk?
choosing an inappropriate method, or applying a data analysis method incorrectly (are the descriptive and diagnostic analysis methods the correct methods? Were the analyses performed correctly)
What is data risk?
choosing inappropriate data, or data that are incomplete or incorrect (are the transaction data we plan to analyze complete and accurate)
What are examples of how data analytics is used in tax accounting?
data analytics is used to help with tax compliance; automation of data gathering for tax compliance can help speed the process, leaving the tax accountant with more time to do tax analysis and planning; and dashboards can help organizations monitor real-time
What does the analysis stage include?
data preparation, building information models, and exploring the data
What data will rank higher?
data that are both relevant and available
What are four potential risk areas?
data, analyses, assumptions, and biases
What does predictive analytics use to identify the likelihood of future outcomes based on historical data?
data, statistical algorithms, and machine learning
What differentiates accountants from machines?
in-depth accounting and business knowledge
What are internal stakeholders?
individuals or groups involved in a businesses' operations; they include an organization's managers and employees
What are external stakeholders?
individuals or groups outside the company; examples include investors and creditors, regulators, organizational partners (clients or customers, suppliers, outsource partners, and donors), and community leaders and members
What does the result of diagnostic analytics do?
inform decision-making about actions in the future
What are the two categories of data?
internal data and external data
What do managerial accountants deal with?
internal reporting and performance analysis
What is descriptive data analytics?
investigates what is happening currently or has occurred in the past (what were gross sales by region for the past two years)
What are two key features of SSBI software?
it provides extended data processing capabilities for preparing data, analyzing data, and reporting data analysis results and it is easy to use
What can management accountants do with SSBI software?
more easily use data to help identify and manage risks, improve budgeting and forecasting (by using more data), and automate internal reporting
What will the new CPA exam include?
more technology and data analytics in both the core and the discipline exams
What does a clear objective do?
narrows the analysis' focus, and specific questions that guide the analysis can be developed based on it
What are examples of information modeling?
net income, profit margin, total assets, or even break-even point in sales dollars
What is assumptions risk?
not understanding or evaluating assumptions about the data or the results (what assumptions were made when collecting data, and are they correct; for example, are we assuming that we have all the data; are we assuming that the 2023-2024 results are as expected; perhaps they were higher than expected, and the 2024-2025 results did not decline as we initially thought)
What is transforming?
occurs when data are cleaned, restructured, and/or integrated with other data prior to using it for analysis
What else can SSBI software also help identify?
operational improvements and create dashboards of key performance indicators (KPI)
What are knowledge gaps to identify?
recognizing when more knowledge is necessary to complete the analysis, acquiring knowledge from a reliable source, and learning how to correctly apply it to the data analysis
What do both internal and external auditors use analytics to perform?
risk assessment and substantive procedures that support the assertion that the financial records of an entity are complete, valid and accurate
How are auditing procedures also changing?
since many firms are investing in robotic process automation software (RPA) and analytics automation software to automate manual audit tasks, auditors can focus on analysis and providing valuable insights
What can save accountants countless hours of tedious work?
software such as Alteryx
What does using automation software to perform routine financial accounting functions such as recording journal entries, creating trial balances, doing preliminary account analyses, and creating financial statements let accountants do?
spend more time analyzing data for insights
What are the six recursive elements to consider when performing data analytics?
stakeholders, purpose, alternatives, risks, knowledge, and self-reflection
What is reasoning?
the human process of logically forming conclusions, judgments, or inferences from facts
What is information?
the knowledge gained from the data
What is extracting?
the process by which data are retrieved from a source; this could be downloading an Excel file or extracting data from a database or a data warehouse
What is data analytics?
the process of analyzing raw data to answer questions or provide insights
What is loading?
the process of importing transformed data into the software used to perform analyses; there are many types of analysis software available, including Excel, Power BI, and Tableau
What is internal motivation?
the project is motivated by a desire to better serve a client, better understand phenomena to gain business intelligence, or to perform job responsibilities (projects are motivated internally when the incremental information gained is believed to outweigh potential costs involved with performing the data analyses)
What is external motivation?
the project originates from a request or requirement by another party, such as external stakeholders (could be investors, creditors, supply chain partners, industry regulators, or government agencies); someone internal to the organization, but on a different team, assigns the project
What is an objective?
the project's goal
What is the purpose element?
the reason driving the questions for the analysis; focusing on the purpose helps select the best data, analysis, interpretation, and communication options
What are stakeholders?
those individuals or groups with an interest in the outcome of a data analysis project (can be internal or external)
How can data analytics be used in tax accounting?
to analyze tax efficiency of business units, identify tax opportunities, and aid in evaluating global opportunities
What is the goal of the report stage?
to determine if the analyses met the project's objectives and then to share the results
What is the core goal of data analysis?
to explore data to identify patterns, trends, or unusual observations
What skills does communicating data analysis results require?
writing clear and effective memos and reports, preparing successful presentations, creating meaningful data visualizations, and telling compelling data stories
