Different Types of Data Analytics for Business Decision Making
In organisations all over the world, data analytics has evolved into a powerful tool. Data analytics can help businesses learn more about themselves. It can assist them in improving their strategies and streamlining their decision-making processes.
There are different types of data analytics. They all offer different kinds of support to businesses for them to succeed.
Here, you will learn about four types of data analytics for better business decision making.
1. Descriptive Data Analytics
Descriptive data analytics is the simplest type of data analytics and serves as the foundation for all other types of data analytics. It aims to answer the question ‘what happened’. Businesses frequently use this type to understand past events and customers.
For instance, assume you’re analysing your business’s data and discover a seasonal spike in one of your products: a watch. In this case, descriptive analytics can help you identify the months of the year when your product sales increase.
This type of analytics helps businesses analyse raw data and provides insights into a company’s performance.
2. Diagnostic Data Analytics
If descriptive analytics tells you what happened, diagnostic analytics tells you the next logical question ‘why did this happen’. This type of data analytics is used by businesses to understand the root cause of a problem within their organisation.
Continuing with the previous instance, you could look into the demographic data on watch users and discover that they are between the ages of 20 and 40. Customer data analysis reveals that the primary motivator for customers to buy the watch is to gift it to their loved ones. And the spike is due to the holidays, which include gift-giving.
Diagnostic analytics helps businesses determine the cause of all positive and negative anomalies in businesses’ sales or performance.
3. Predictive Data Analytics
Predictive analytics is a more advanced form that helps answer the question ‘what will happen next’. Businesses use it to forecast the future outcome of a situation using all available data.
For instance, knowing that your watch sales increased during the holiday season provides you with sufficient data to predict the same trend will occur next year. This reasonable trend, supported by data, will help your organisation make necessary decisions in the future.
This type of analytics helps businesses make educated predictions about what the future may hold for them and develop strategies based on likely scenarios.
4. Prescriptive data analytics
This final type of analytics answers the question, ‘what should we do next’. Businesses use prescriptive analytics to take an actionable course to improve their performance after analysing the available data.
Completing the watch instance, what should your organisation do given the predicted seasonality due to holiday gift-giving? Imagine your organisation decides to run a specific test with two ads, one aimed at customers of a younger age group and the other at customers of an older age group. The data from that test can help them determine how to capitalise on the seasonal spike and its alleged cause even more effectively.
Thus, prescriptive data analytics helps businesses take a course of action that can help them to perform better in the market.
Depending on the situation, data analysts use the four types of data analytics in tandem or two or more types to create a complete picture of organisations and make informed decisions. Therefore, every business requires skilled data analysts to understand the problem and determine the best solution for the business’s growth and success.
So, if you are an aspiring data analyst who wants to learn the skills and methodologies of data analytics, you might benefit from enrolling in one of the best online analytics courses in India. These certificate courses from globally renowned institutes will help you build a strong foundation in data science and analytics.