Data analytics techniques are popularly used by accountants to assist companies in making better informed business decisions. Data analytics (DA) is the exercise of scrutinising data sets in order to recognise trends and come up with a workable interpretation from the information they offer.
The accountant will start off with descriptive analytics, which is the assessment of current and historical data, to answer basic questions, such as “What happened?”
Specific patterns can be identified within the data. This data will include tables, line graphs, pie charts, bar charts, etc. (Traditional business intelligence can also be referred to as Descriptive Analytics.)
Following on from there, diagnostic analysis will be applied to determine why a certain trend/outcome happened. This form of analytics is aimed at answering the question of “Why did it happen?”
When what has occurred is clearly understood, the company can then predict what is likely to happen in the future, by employing predictive analysis. This is an advanced type of analytics, whereby the accountant will use techniques such as forecasting, regression analysis, pattern matching, etc.
After all the above levels of analyses have been completed, prescriptive analytics is then applied to obtain an answer to, “What should be done?” – This will include graph analysis, etc. A satisfactory outcome to prescriptive analysis depends hugely on the successful accomplishment and accuracy of the previous analytical steps.
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