Data Analytics is one of the tools that should receive the most attention from the companies that want to increase their competitiveness in the market. This technology makes it possible to not only optimize your decision-making process but to also map out and implement projects and strategies more securely and efficiently.

Are you interested in learning more about this innovation? Continue reading this article and find out what Data Analytics is and how it can benefit your company!

What is Data Analytics?

Data Analytics is basically the process of analyzing all the data and information that makes up Big Data, to identify patterns and insights that can revolutionize the operations of a company.

For example, with the tool, the marketing team can gain a deeper understanding about the reality and purchasing patterns of its potential customers. This allows them to create more efficient campaigns, improve their brand image and increase their number of sales.

Given these characteristics, it is easy to realize the importance of data and information analysis in planning and executing Business Intelligence strategies.

How does this tool work?

Enabling data analysis requires the company to hire Data Analytics experts and provide them with tools such as artificial intelligence and machine learning solutions to start the data mining process.

Once the software identifies interesting patterns, they are corroborated by data analysts who should use the information to advise management and guide various processes.

As technology advances and the information verification process becomes more intuitive, companies have empowered their employees to perform simpler data analysis that doesn’t require as much expertise.

This has allowed for Data Analytics professionals to stay focused on more strategic projects, with the potential to generate greater impacts for the company.

How important is Data Analytics for businesses?

This technology is fundamental for companies, including smaller ones. By intelligently allocating your resources, you can avoid losses and gain better results.

Check out how the benefits of the tool works.

Demand forecast

One of the most important tasks of the management team is to verify the actual demand for their products. After all, when the manufacture of an item is higher than its output, it ends up stuck in stocks, suffering breakdowns and generating costs to the company.

Through Data Analytics, analysts can study a range of useful data, such as historical sales patterns and the current reality of the market, to more accurately point out the amount of items that should be produced. This allows the company to reduce its costs and optimize its available resources.

Cost identification

Intelligent use of resources also requires that all unnecessary costs and waste be eliminated. The big issue is that some expenses are so diluted in the company’s processes that it is virtually impossible to identify them.

Fortunately, Data Analytics provides the management team with a much more complete view of how the company works and how all resources are used. Given this, it is easier for professionals to detect even so-called ‘hidden costs’.


Every day, managers and entrepreneurs need to make a series of decisions with the potential to completely change the situation of the company. For this reason, it is natural that they want access to accurate and reliable information, so that their choices are as successful as possible.

In this context, Data Analytics emerges as an important source of data for grounding strategies. By making use of it, managers can make smarter decisions, which will avoid losses and bring more positive results.

What analysis can be made in Data Analytics?

Because the operation of a company has several processes, a single solution would not be able to meet all of them satisfactorily. That’s precisely why Data Analytics can run in four different ways.

Next, find out how each of the type of data analytics works!

Predictive analysis

Predictive data analysis uses statistics and data mining to understand how the verified item is likely to behave in the future. For example, through it, the management team is able to create sales projections based on the analysis of the consumption patterns of its customers.

Prescriptive analysis

Prescriptive analysis makes use of graphs and behavior simulations in order to identify events that are occurring and understand the logic behind them. Using this concept, managers can check, for example, the items and products most demanded by the market at the moment.

Descriptive analysis

Descriptive analysis uses data mining technology to understand an event that occurs in real time, that is, it can be used to check the latest state of the analyzed item. An example of its application is credit analysis, which requires a verification of the payment terms of the debtor party.

Diagnostic analysis

Finally, diagnostic analysis makes use of solutions in data mining and information correlation with the objective of understanding an event of the past. This opens space for companies to repeat positive results and avoid crisis situations.

As examples of its implementation, we can mention the preparation of commercial reports or even the study of the stock prices of a given company.

In fact, Data Analytics has the potential to optimize a company’s operation, but it is worth remembering that the success of its implementation is directly linked to the solutions used by data analysts. Therefore, it is necessary to have highly efficient software developed by serious and experienced companies in the field.