In today's highly competitive world, businesses are constantly looking for tools to help them make better decisions.

Business analytics, or business data, is one of these tools, as huge amounts of data are generated every day and are required to be processed.

In fact, according to research, companies are using data in order to:
 

• Improve their processes (60%)
• Improve their strategy (57%)
• Improve their financial performance (52%)
   

But it is vital that professionals learn to "read" this data correctly in order to get the best results.
But before we delve further into the world of business analytics, let's start with the basics.
 

 What is Business Analytics

Business Analytics is the process where a company uses methods to process data and draw conclusions in order to make better business decisions.

These methods vary and can be data mining, predictive analytics, machine learning and many more.

Of course Business Analytics is under the umbrella of Data Analytics that many professionals need for their work.

But who are these professionals?

• Marketers (analyze customer data, market trends, marketing campaigns)
• Product Managers (analyze customer and market data such as feedback, in order to improve products)
• Financial Managers (analyse macro and microeconomic data to prepare budgets and financial forecasts)
• HR Managers (analyse data from employees such as opinions and feedback to improve working conditions)
   

Of course, there are many more professionals who apply data science to their work and it is also worth discovering this industry if you haven't already.

Let's now look at the types of business analytics that exist.
 

 The 4 Types of Business Analytics
 

1) Descriptive Analytics

Descriptive Analytics is the simplest type of data and the basis of all the others.

They are related to the analysis of various performance indicators in order to understand a current situation.

In a nutshell, descriptive analytics answers the question: "What's going on?"

The most common output of descriptive analytics is a report with charts to help understand the current situation. 

For example, a company may identify that the demand for its children's toys increases particularly at Christmas each year, so there is seasonal demand.

This can be represented in a diagram:
 

You can see how in December each year demand increases and then drops dramatically.

Data Visualization in general is a very useful tool for graphically understanding data.
 

2) Diagnostic Analytics

Diagnostic Analytics answers the question: "Why is this happening?"

This type of Business Analytics uses techniques such as data mining, data mining and correlation to identify root causes of events.

Continuing our previous example, through this analysis we will look at why this seasonal demand for games is occurring.

That is, the data will be related to customer age, season, questionnaires, advertisements and so on.

In other words, with diagnostic analytics we get to the root of an issue, which is very useful for businesses.
 

3) Predictive Analytics

Predictive Analytics is used to predict future trends and events and answers the question: "What will happen in the future?"

By combining analysis of historical data and market trends, businesses make predictions and make decisions based on them.

For example, knowing that the demand for children's toys increases every Christmas, a company can predict that the same will happen in future years.

With predictive analytics one can create strategies based on possible scenarios.
 

4) Prescriptive Analytics

Prescriptive Analytics answers the question: "What is the next move?"

They take into account various factors and suggest possible alternatives. Something particularly useful when a business makes data-driven decisions.

Continuing our previous example, the company needs to decide what to do based on seasonal demand. It can for example increase its advertisements, change the product slightly or anything else based on the data available to it.

So it becomes clear that Business Analytics is not only something helpful, but now necessary for businesses and professionals if they want it:

 

• Make better decisions
• To increase their revenues
• To increase their revenue and improve their processes
   

Let's summarize.
 

 In a few words

So we've seen what business analytics is, what its types are and how it helps a business grow.

This is why it is now vital for professionals to be trained in Data Analytics if they don't want to be left behind in the job market and apply their knowledge to a company.

Therefore, if you want to take the next step in your career, you can discover the comprehensive Professional Diploma in Data Analytics that we have created and enroll immediately!