The Role of Big Data in Accounting

Big data and related technologies are transforming the field of accounting. Leveraging insights gained from big data analysis can advance accounting practices in dynamic ways. Data-driven accounting can dramatically improve decision-making and positive outcomes for businesses and clients. This intersection of big data, information technologies and accounting processes is an essential aspect of high-level study and practice in the field.

Accordingly, the online Master of Business Administration (MBA) in Accounting program from Fitchburg State University explores accounting information systems and related technology developments. Combined with the exploration of accounting theory, finance and strategic management, these contemporary studies prepare students for success in the evolving profession.

What Is Big Data?

“Big data” is often used as a buzzword phrase to encapsulate many of the technological advancements transforming accounting and modern business in general. But big data is a specific and important concept.

Tech giant Oracle defines big data as “data that contains greater variety, arriving in increasing volumes and with more velocity.” These three Vs of “big” data differentiate the concept from relatively small-scale datasets of old: volume, velocity and variety. There is simply much more data created in today’s digital world, from far more diverse sources, than was previously imaginable.

This proliferation of data can be a boon for data-driven businesses. But, by nature, big data is largely unstructured, unorganized and entirely too complex for past technologies to process. As Oracle puts it, “Data has intrinsic value. But it’s of no use until that value is discovered.”

This concept highlights the importance of modern advancements in artificial intelligence (AI). Branches of AI like machine learning (ML) and natural language processing (NLP) enable the development of advanced data analytics technologies to gather, organize, process and analyze big data readily.

In this way, the marriage of big data and advanced analytics technologies can transform otherwise overwhelming, unusable quantities of data into usable information and insight. Business intelligence tools and technologies like data visualization further help business users explore, understand and discover data and its insights.

How Can the Use of Big Data and Related Technologies Improve Accounting Practices?

One of the most straightforward, impactful technologies in accounting and finance sector applications is robotic process automation (RPA). With RPA, advanced AI software can automate many repetitive tasks, like data entry, as well as more complex tasks involved in auditing and other accounting practices.

This streamlines and exponentially increases the efficiency of mundane accounting processes. RPA also helps reduce errors common to manual data entry, improving process speed and accuracy as well as the resulting quality and timeliness of insight gained from analysis. Plus, with the ability to detect outliers in vast datasets, RPA and big data analytics help accountants move past the limits of narrow audit sampling.

The speed and scope of AI-driven RPA and big data analysis enable accounting insight delivery in near real-time, on demand. This availability means decision-makers get the information they need when they need it. Plus, accountants are freed up to do more impactful work. The accountant’s role becomes more of a strategic advisor than a number cruncher, helping translate big data analyses into strategy formulation insight for clients and businesses.

An Institute of Management Accountants (IMA) survey found that 70% of respondents who have implemented big data into practices use it to inform strategy formulation. Improving business decision-making and strategy is the real benefit of data analysis. Deploying big data capabilities to analyze large amounts of complex finance and accounting data can maximize the perspective and insight gained for strategy formulation.

All of IMA’s survey respondents that have adopted big data analysis use it to improve performance measurement. This is a key component of accounting practices, with numerous variables and inputs that make objective evaluation challenging. Big data analysis can quickly integrate myriad inputs, improving efficiency, accuracy and objectivity in performance measurement.

Big data and analytics can help manage risk. AI technologies provide powerful predictive analytics. With big data and analytics, professionals can correctly predict the risk involved with investments and other financial activities. Prescriptive analytics help accountants understand the best course of action to mitigate risk.

An article from TDWI’s Upside highlights what may be the most important, overarching benefit of big data in accounting: improving the client experience. Big data and analytics technologies help accounting firms offer clients more accurate and impactful services. With aggregated, industry-wide data analysis, accountants can also better quantify and contextualize performance metrics for clients.

Again, these technologies afford accountants more time to spend advising clients directly. This extra consultation adds value to the client-business relationship. Along with providing cutting-edge, data-driven services, fostering client relationships, retention and loyalty are also vital to success in accounting.

Learn more about Fitchburg State University’s online MBA in Accounting program.

Related Articles

Have a question or concern about this article? Please contact us.

Our Commitment to Content Publishing Accuracy

Articles that appear on this website are for information purposes only. The nature of the information in all of the articles is intended to provide accurate and authoritative information in regard to the subject matter covered.

The information contained within this site has been sourced and presented with reasonable care. If there are errors, please contact us by completing the form below.

Timeliness: Note that most articles published on this website remain on the website indefinitely. Only those articles that have been published within the most recent months may be considered timely. We do not remove articles regardless of the date of publication, as many, but not all, of our earlier articles may still have important relevance to some of our visitors. Use appropriate caution in acting on the information of any article.

Report inaccurate article content: