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Companies generate huge amounts of data that must be processed to produce readable information and results.

Big data analytics in accounting is a game-changer as it improves risk identification and real-time access to data and reports.

More and more companies are adopting more and more new technologies to make them more efficient. This includes blockchain, artificial intelligence, machine learning, robotic process automation, data analytics, and more. The use of traditional accounting has turned the accounting world upside down, but with the advent of big data analytics, it has taken leaps and bounds, tapping into the untapped potential of any business.

Use Cases of Big Data Analytics in Accounting

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Companies accumulate huge amounts of data that can reach petabytes and zettabytes. The accounting function of any organization records all types of financial and non-financial transactions, collects and analyzes them using predictive models to find actionable insights. Data analytics is all about making sense of the received data and hence, it takes the hassle out of traditional accounting. Let’s take a look at why you would need to transition your business from using conventional analytics to using big data.

1. Real-time reports

One of the biggest USPs of using big data analytics in accounting is its real-time reporting functionality. Most analytics tools available today are cloud-based, making real-time insights and reports more accessible than ever. As Big Data deals with a wealth of data, it analyzes historical data in terabytes and even petabytes to find actionable insights.

2. Real-time access

Another feature of using data analytics in accounting is real-time access. As it is cloud-based, it has the advantage over data visibility timers in different functions of an organization. It is possible to access it simultaneously and different users can have different access privileges.

Other than that, data syncs so that changes made to one node are easily accessible on other nodes. This improved access to real-time information with transparency facilitates decision-making.

3. Risk identification and mitigation

Certain risk factors can prevent a company from outperforming the revenues it received last quarter or compared to its competitor. Big data can help find risks associated with financial services, such as supply chain, fraudulent transactions or activities, liquidity, data breach, etc. Companies can use all the data and add it to various algorithms to anticipate or predict possible outcomes or track fraud. book activities. As accountants can now detect errors and risks earlier, the chances of it spreading from the point of no return decreases.

4. Data visualization

It’s impossible to make sense of big data without using tools like Tableau. It is a widely used data visualization tool for Big Data, as it helps to find the flow, pattern, and irregularities in the data set. Analysis of the visualized data can help in making business decisions and strategies to adhere to in the future.

Conclusion

Big data analytics in accounting can be an important driving force for many use cases. It includes forecasting sales performance on food, travel, hospitality and others across different data sources, such as Booking.com, Yelp, etc. It can reduce downtime and operational costs by monitoring IoT sensor data.

Businesses can use data analytics in accounting to weed out fraudulent activity. Optimization of labor and personnel requirements is another problem that can be mastered with the help of big data based on forecast analysis.

Organizations around the world are leveraging the power of big data analytics in accounting over the traditional approach. This is because of the many benefits it brings to the table, including real-time data access and reporting, data visualization, data audits, and more.