Can Accounting and Finance Teams Effectively Use Big Data?
Across industries, throughout businesses lines and within departments, companies are investing in data collecting technologies and solutions like never before. That’s because business leaders are realizing that actionable data generates significant strategic advantages throughout the enterprise.
As the desire to collect more and more data has advanced, so too have the technology tools that make doing so possible. But while the tools can collect an impressive amount of a business’ information, they can’t impart better business results.
Instead, it takes skilled professionals who understand the data being collected just as well as they do the technology that’s doing all of the collecting. And nowhere is this more evident than in the accounting and finance industry, where success hinges equally on the acuity of quantitative tools and on the quality of human intelligence to employ those tools.
The Evolution Of Data Storytellers
This dichotomy has given rise to a new generation of professionals who can bridge the disconnect between finance and technology. These professionals can turn raw information into meaningful insight, thousands of data points into refined business priori- ties and unintelligible numbers into real, powerful business intelligence. As a result, they’ve pushed the role of big data beyond the technological limitations of collection and into the realm of consultation.
Information, about customers, competitors, products and industry trends, has driven business results throughout history.
Decades ago, the introduction of digital data processing moved information from file cabinets to technological platforms. More recently, processing power and computing architecture have advanced considerably, pushing the limits of the amount and types of data that can be collected. As a result, the scope of accessible data today is both immense and diverse.
Older technologies addressed data that was similarly structured, so comparisons were generally between digital apples and apples. By contrast, today’s “big data” can take many forms and draw on a range of sources. Not only can users mine a vastly larger terrain, they can find related information in a variety of formats.
Two Different Sources of Big Data in Finance:
SQL Databases: Tech Departments mine information the company has already achieved.
Stream-processing: Captures data that runs through a system in real time to reveal information about the current state of an enterprise.
A lot of similarities:
- Both rely on computational power and storage based on many computers running many processes in parallel.
- There are numerous open source and proprietary solutions for both sources.
- Both require big storage solutions to accommodate the large amounts of data collected.
- Both offer value to accounting and finance professionals who need to manipulate historical data to determine existing trends and identify financial events that are occurring in real time.
Big data in finance and big data technology are transforming the nature of analytics in every field that relies on large, heterogeneous data sets, from government agencies to police forces to the private sector. Accounting and finance departments in particular are among the biggest beneficiaries of big data.
Consider a search for credit card billing transactions. Traditionally, looking up this data was easy if, and only if, the data was in a static archive and organized in the same columnar format. Big data, however, allows businesses to seek out credit card information in a variety of formats, both archival and as it’s being processed in real time.
In addition, more granular financial data than ever before is at the disposal of financial departments. When it comes to auditing financial performance across the enterprise, big data software frameworks afford companies a detailed look at relationships among myriad data of very different types.
Accounting and finance departments can now perform immensely complex queries based on very large data sets; these inquiries are limited only by the protocols programmers write queries for. Professionals can watch for changes and trigger events that are much more fine-grained and fast-moving than ever before. Companies can identify fraud, transactions and other elements in real time, generating and protecting millions of dollars within minutes.
The promise of big data should be alluring to any accounting and finance team that understands the strategic advantage of data sets that are deeper, wider and more current than anything it’s handled before. However, access to the data doesn’t automatically translate into command of its significance. Financial data sets may grow more complex, but that doesn’t add up to actionable business information without the human intelligence to direct it.
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