The appliance of data science

Primarily, this is because of a need for data science and data analytics… but why is it the case? First of all, we need to ask: what is data science? Data science is a field that involves evaluating large data sets and drawing conclusions from them.

Data scientists can interpret data, evaluate its precision, and distinguish patterns and developments by using both statistical techniques and instruments. Any accountant or financial professional would agree that, after the calculator, their main tool has been Excel, but data science has moved things forward. Now, since the fourth industrial revolution, we hear talk of blockchain, artifi cial intelligence (AI), machine learning and robotic process automation (RPA).

Accountants are known for adding value to decision-making. Businesses of all sizes need people with data analytics skills who are willing to challenge the status quo. While management accountants won’t necessarily focus on becoming data scientists, they do require improved data science and analytical skills in order to derive insights from data and enable more effective decision-making and control.

When looking at data analytics, it comprises four components. First, we have descriptive analytics. This is about past and current data which provide us with detail of what is actually happening. Secondly, we move through diagnostic analytics - which shows ‘how’ things happened. 

Thirdly, we progress to predictive analytics. This shows what is going to occur or what will be the outcome. Finally, we have prescriptive analytics, which show what needs to happen to effectively ‘match’ the forecast.

Indeed, accountants can become excellent data scientists given that they are very attentive to details and have many numerical technical skills. They would be very adaptable to the four types of analytics we mentioned above.

Additionally, they are often problem solvers. They often adjust to suit changing conditions. Accountants will use data analytics to assist businesses in discovering additional insight and highlighting operational efficiencies. Firms that are increasingly data-driven will connect their clients by addressing their needs.

Time being spent on monotonous data entry is better spent promoting clients’ companies, or their own growth prospects. Big data could be used to unravel behaviour patterns in customer and business developments, which can identify profi table investment opportunities. Blending data analytics, data science and accounting could be crucial to your professional success.