Data analytics can help businesses to uncover valuable insights within their financials, identify process improvements that can increase efficiency, and better risk management. Data analytics can add value to the business decision making within the organization. The true value of data analytics comes not at the point when the data is compiled, but rather when decisions are made using insights derived from the data.
Types of Data Analytics
1. Descriptive analytics
It provides insight based on past information. What is happening?
Used in standard report generation and in basic spread sheet functions such as counts, sums, averages and percent changes and in vertical and horizontal analysis of financial statements.
2. Diagnostic analytics
Examine the cause the past results. Why did it happen?
Used in variance analysis and interactive dashboards to examine the cause of past outcomes.
3. Predictive analytics
Assist in understanding the future and provides foresight by identifying patterns in historical data. What will happen? When and why?
It can be used to predict an accounts receivable balance and collection period for each customer and to develop models with indicators that prevent control failures.
4. Prescriptive analytics
Assists in identifying the best option to choose to achieve the desired outcome through optimization techniques and machine learning. What should we do?
Used in identifying actions to reduce the collection period of accounts receivables and to optimize the use of parables discounts.
Data analytics can be used to aggregating information to create a picture of an organization that summarizes the details contained in each transaction. Working with descriptive analytics, predictive analytics, and prescriptive analytics comes more beneficial for the business to take decisions in correct manner and on correct time.