A fundamental aspect of accounting is helping clients comprehend what financial information means in the context of past, present and future business outcomes. Translating complex financial data and analyses into understandable information for business users can be challenging. Advancements in data analytics and data visualization tools, however, make this and other aspects of accounting more efficient, impactful and beneficial.
The online Master of Accountancy (MAcc) Data Analytics/Data Visualization Track program from Northern Kentucky University (NKU) reflects the increasing importance of accounting data analytics technologies. The program combines the study of advanced accounting topics with the exploration of data analytics and visualization, business intelligence (BI), and business analytics. With this integrated knowledge, graduates excel in the dynamic role accountants play in today’s data-driven business world.
For the modern accountant, the ability to visualize and analyze data is central to delivering value for clients. The following are three important ways data visualization and analytics support that work.
1. Provide Clients With a Snapshot They Can Understand
Accounting, at its core, is a practice of gathering, organizing and analyzing data. Advancements in computing vastly increased both the amount of data available and the capabilities of data analytics technologies. Logically, accountants use these technologies to make their work more efficient and draw more complex insight from the data stories they uncover.
Accountants must communicate findings from financial data analyses to their clients. Yet clients may not possess a high level of data literacy, making effective communication difficult. This is where data visualization can be beneficial.
Through the use of advanced software, accountants can render complex data into simple visual forms, using colors and shapes to demonstrate relationships between data. A visualization could be a traditional pie chart, graph or 2D area visualization, such as a dot distribution map, to demonstrate market penetration in different regions.
The types of data, user preferences or competencies, analysis goals, and other variables will determine what kind of visualization would be most useful. The intent is to help users understand data analysis in a form that best conveys the information clients need.
2. Help Clients Visualize What May Come
Visualizations of financial data can help clients easily understand what happened (descriptive analytics) and why it happened (diagnostic analytics). This is essential for monitoring and responding to business performance metrics, operational efficiency and optimization goals, customer behavior, and more.
Clients also want to understand what is likely to happen (predictive analytics) and what they should do about it (prescriptive analytics). Driven by artificial intelligence (AI) technologies like machine learning, modern data analytics software analyzes information from myriad sources to deliver advanced analyses.
Using predictive data analytics and tools such as time-series visualizations, accountants can help their clients get a good sense of potential trends. By applying prescriptive analytics to data, accountants can show clients probable outcomes for different variables, such as the potential financial return on an investment in equipment or employee training.
Visualizing these outcomes projected over time can help clients make informed decisions based on value-added insights. This function could be an advanced or more dynamic form of forecasting, integrating accounting, business analytics and BI.
3. Empower Clients to Explore Data on Their Own
Data visualization and technologies also help business users understand data and gain insight through modern BI tools. Businesses may embed these applications within various office software platforms or make them accessible through dashboards.
Business users can apply these tools to produce visual displays of information. With BI applications that leverage natural language processing and generative AI, users can employ spoken language to “ask” questions about data, triggering predictive or prescriptive analyses in visual form. BI tools can anticipate users’ preferences and likely data analysis requests by predicting trends or anomalous factors that might interest them.
Integrating and utilizing such tools requires collaboration among accountants, data scientists, information systems professionals, business analysts and others. These professionals also help coach top leadership and managers to use such technologies effectively, derive insight and make accurate data-driven decisions.
AI-driven analytics software can also automate much of the mundane reporting work that consumes accountants’ time. This allows accountants to spend more time on other essential, hands-on tasks that directly benefit clients.
Why Is Data Visualization a Core Accounting Skill?
Taken together, modern data analytics helps accountants discover financial insights more effectively and efficiently. The diverse types of data visualization methods allow accountants to communicate those insights to clients clearly, quickly and in usable forms. In turn, clients can make informed business decisions based on accurate financial information and analyses that are clear and easy to understand.
For accountants who want to meet that demand, building expertise in data analytics and visualization is no longer optional. It is central to the profession, as reflected in the current, tech-driven iteration of the CPA Exam. NKU’s data analytics and visualization MAcc specialization targets this precise area of expertise, preparing graduates for the analytical and communicative demands of modern accounting practice.
Learn more about Northern Kentucky University’s online Master of Accountancy Data Analytics/Data Visualization Track program.
