The Role of XBRL in Overcoming Challenges of Big Data

  • According to a survey report, the total amount of big data consumed globally is expected to increase from 79 zettabytes in 2021 to 180 zettabytes by 2025.
  • Almost 95% of the companies require expertise in handling these sets of unstructured data.

Source: https://www.analyticsinsight.net/top-10-big-data-statistics-you-must-know-in-2021/

Is big data helpful to businesses? Yes! Is it being used effectively? No! Unsurprisingly, most of this data goes unused. However, with the increasing relevance of big data in financial reporting, it is undeniable that companies will have to find ways to cope with this massive big data explosion in the coming years.

Here, the first question that might run in your mind is how big data benefits financial reporting. Let’s find out.

 

Big Data and Its Role in Financial Reporting

Since the beginning of time, financial reporting has always been the focus for companies. Why? Because financial data helps businesses gain a lot of insight into business activities like the number of items purchased, the total spend and profit of the department, and more. However, this data only hints at the future, leading to much guesswork based on the observed patterns. For companies to make data-driven decisions about the future, it needs to collect data in the context of the world in which the business exists.

This is where big data comes into play.

Big data collects information from various sources and layers them to understand what is happening by identifying the trends and patterns. These sources are traditional, like demographics and organizational data, and less conventional, like social media. However, it becomes nearly impossible to identify trends using traditional reporting techniques like spreadsheets and flat databases with massive data.

Enter XBRL…

Overcoming the Challenges of Big Data With XBRL

Despite the various benefits of big data for companies, it faces some challenges as well, which include:-

  • There Aren’t Enough Experts

One of the significant issues in tackling big data is the lack of experts who can handle and analyze the massive amount of data generated by the company, leading to the ineffective use of big data.

 

  • Absence of Structured and Standardized Data

Another challenge of big data is that it generates data in all different formats, which is unreadable by machines. To enter the data into accounting systems, you will first have to standardize the unstructured data.

 

  • Data From Various Sources

When the data is received from several sources, it becomes increasingly difficult for companies to analyze the accuracy of the data.

However, with XBRL in the picture, it becomes easier for companies to standardize large amounts of data and convert them into a machine-readable format. Standardized data help organizations to compare data more accurately. In addition, the tagging feature of XBRL assists regulators in detecting risks and frauds at an early stage based on the rules laid out by the regulatory bodies. By saving a lot of time and resources on standardization, it helps businesses to focus more on analyzing their data sets and other core business activities. The best part? Machine-readable languages like XBRL have also made it easy and cost-effective to analyze the data and allow better access to data.

 

XBRL – The Path to Handling Big Data

With the escalating amount of big data, it has become vital for businesses to understand the role of XBRL for effective financial reporting. Or, if you want to focus on your core activities, all you need is a trusted service vendor.

DataTracks’ XBRL service can help you convert your financial reports into XBRL format for submitting to ACRA, Singapore’s Accounting and Corporate Regulatory Authority. With experience of more than 16 years, DataTracks has successfully prepared more than 200,000 reports for more than 19,900 clients worldwide. To know more about their XBRL services, get in touch with an XBRL expert @ +65-31-582-850 or email at enquiry@datatracks.com.sg.

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