The Vital Role of Data Analytics in Company Finance

The role of data analytics in company finance is only growing with every passing year. Data analytics professionals can now use statistical modelling, machine learning, and data science to help organizations reduce risk and make profitable and efficient business decisions. Data analytics provides instant insight to improve the quality and speed of decision-making to drive better business results.

According to a Research and Markets report, the global Big Data Analytics market is expected to reach $105.08 billion by 2027, growing at a CAGR of 12.3% from its 2018 market value of $37.34 billion.

Businesses across the world are increasingly adopting data analytics, especially for functions like finance. The growing need for timely information based on which enterprises can make efficient financial decisions is one of the primary reasons for its growing popularity.

Finance plays a crucial role in the growth of every business. Data analytics and its tools, like statistical modelling, machine learning, and data science, helps finance professional with insights to understand the future risk and opportunities resulting in timely decisions.

Why Data Analytics for Finance?

Technologies have evolved rapidly in the last few years. Supercomputers of the past are now the everyday desktop computers that we use at work and home. Everyone now has the ability to collect data. But from the point of view of business finance, what good is millions of bytes of data if decision-makers cannot decode it?

Data analytics in finance has many advantages:

• Improve cash flow by reducing credit risk and identifying opportunities across the credit portfolio
• Automate decisions to manage risk, receivables, and collection priorities with online financial data
• Synchronize the flow of information across all your financial systems for better & faster decisions
• Streamline and shorten the due diligence process on new deals and acquisitions
• Transform finance from "sales inhibitor" to "sales enabler" with a shared view of risk and opportunity
• Access all relevant financial data online within your ERP and accounting applications

Introduction of Data-as-a-Service (DaaS)

While data analytics can offer a host of business benefits, not every organisation has the infrastructure or professionals to benefit from it. This led to the creation of Data-as-a-Service (DaaS). From data management, integration, analytics to storage, DaaS is becoming increasingly popular among global businesses that want to benefit from the data analytics revolution.

Daas is similar to Software-as-a-Service (SaaS) in many aspects. Just like SaaS eliminates the need for businesses to run business applications locally, DaaS outsources the majority of the data processing operations, storage, and integration to the cloud infrastructure of the service provider.

Benefits of DaaS for Finance Analytics

Some of the top reasons why businesses are now considering DaaS for analytics in finance are as follows-

• Cost-Savings – With DaaS, it is easier for businesses to optimise their data processing and management costs. Companies can use the cloud resources that they need and only pay for the used resources.
• Low Set-up Time- Building a data analytics setup is a cost and time-consuming affair. With DaaS, businesses can begin data processing and storing almost immediately. This also helps in reducing staff requirements.
• Automated Maintenance- The DaaS providers are fully responsible for the upkeep and maintenance of their cloud infrastructure.

Finance Data Analytics: Empowering Business of the Future

Finance analytics has provided a progressive framework for business predictions, equipping organisations with foresight that can assist them in making critical business decisions. As it can monitor and analyse the consumer patterns and build relevant connections, it also helps businesses personalise their approach.

It is due to these valuable benefits that data analytics and DaaS are getting increasingly popular among organisations. Businesses can consider building a data analytics infrastructure of their own or look for a reputable DaaS solution provider to access the insights and have the predictive ability that could provide them with a competitive edge.