Data analytics is the process of analyzing the raw data in order to draw conclusions to make informed decisions. A set of data gives valuable information about the subject. It quantitatively and qualitatively informs you about what happened, why it happened, what should you do, when should you take the step and where should you apply and more, 

In a business system, getting accurate forecasting is indispensable to run successfully. Data analytics reveal trends and patterns that are crucial for taking the next big decision in the business.  

You might have already heard about an upsurge in the demand of data scientists nowadays. Although, accountants were already performing as data scientists by analyzing, calculating and predicting the financial outcomes. 

Data analytics in Accounting 

With big data driving the business world, accounting domain has started embracing technologies that help them extract valuable information from data sets. This incorporation of data analytics in bookkeeping has increased the efficiency, agility and demand for the accounting platforms. 

To get a clearer picture of the big data, let’s know about the 4 types of data analytics. 

Descriptive analysis 

Descriptive analysis defines the “what is” element of the data. It describes the information and classifies it accordingly. Though descriptive analysis is often misunderstood for data analytics itself, it is an important factor to identify the underlying problems. 

Diagnostic analytics 

In diagnostic analytics, your data is diagnosed deeply. Unlike descriptive analysis which describes the problem in a simple manner, the diagnostic analysis takes an in-depth analysis of the data. This intensive analysis helps to understand the underlying reasons behind certain issues or problems.  

Predictive analytics 

Predictive analysis is the process of predicting future outcomes based on historical data, machine learning, etc. With the help of advanced technologies, organizations are now able to reliably foresee insights.  

Prescriptive analytics

Prescriptive analytics urges you to take action along with predicting the future. This makes prescriptive analytics most significant among the types of data analytics. Rather than just monitoring the data, this method prescribes actionable insights which makes it more efficient.  

Importance of Data Analytics in Accounting Today 

Accounting has been from the ages a way of analyzing the data to make better decisions. You might have already heard about an upsurge in the demand for data scientists nowadays. It is the result of the rapid increase in the volume of data, the importance of big data in business, and more. 

Change of consumer behaviors, buying methods, internet usage, digital shift, etc. Although accountants were already performing as data scientists by analyzing, calculating, and predicting the financial outcomes, the age has come where they have to seek more specialized way of doing so. 

Adopting the mentioned types of data analytics to analyze your accounting data can certainly change the way you gather insights from the data. With tougher business scenarios, it’s high time that businesses start using accounting platforms that embrace advanced technologies like blockchain, AI, IoT, machine learning to make better business decisions and to perform easier & efficient accounting.