What Are The Advantages Of Investing In Big Data?

What Are The Advantages Of Investing In Big Data?

What Are The Advantages Of Investing In Big Data?

Big Data: However, there may be still doubts about why to invest in this strategy and what are the benefits it provides. Discover the advantages below!

More Security For Decision Making

One of the main advantages is greater security for decision-making. The fact is that Big Data, in conjunction with other tools, helps to analyze valuable information that supports strategic planning.

Choices will not be made based on intuition: it is possible to analyze consistent data and design different scenarios to ensure more accurate decisions for the business. All this happens much faster, as the company will have tools to assist in the analysis.

Cost Reduction

Better decisions mean investments with better targeting and optimization in the use of resources. After all, one of the secrets to the success of any business is to be able to maintain the appropriate volume of expenses to deliver quality to the customer, guarantee competitive prices and still have good profit margins.

To achieve these goals, processes need to work efficiently and without bottlenecks. Still, it is essential to anticipate vulnerabilities and problems through predictive analysis, enabling solutions that avoid or, at least, reduce the impacts of unforeseen events.

The Larger Volume Of Stored Data

Another advantage of Big Data is that it expands the volume of stored data that can be analyzed. It is possible to hire specific solutions to help with this, such as management and cloud storage software.

With more data available and the ability to process it and turn it into insights, the company’s chances of having better strategic planning also increase.

Improved Customer Relationship

The relationship with the customer is one of the fundamental points for the success of any business. And Big Data can also help with this task. It is possible to adopt strategies for collecting and analyzing customer data, aiming to observe purchase histories, open tickets, and behaviors, among others.

This allows you to customize the service in routine dealings and create campaigns and exclusive offers. The main difficulty in the relationship is the lack of humanization and the more general treatment. However, based on data, it is possible to create greater proximity and invest in the relationship.

Improved Team Performance

Finally, it is worth highlighting the possibilities of improving team performance. After all, data analysis can observe the progress of processes, identify obstacles and develop improvement strategies. Also, with the right tools, there are chances to automate some tasks — which helps with productivity.

As a result, teams can work more efficiently. This promotes better performance in business processes and even the optimization of results, increasing business profitability. In other words, investing in Big Data tends to bring a great return.

How To Apply Big Data In Business?

It is not enough to know the concept, operation and advantages to use a resource in the best way in the company. You also need to understand how to apply the strategy effectively in the business to reap all the benefits.

After learning what Big Data is, it’s time to learn the main tips to incorporate it into corporate management. The starting point is good planning, to understand the objectives and the paths that must be traced.

Then it’s time to get to the hands-on work — data scientists are essential to help with this task. Here are the steps to be followed:


To get started, you need to define data collection. It is necessary to decide which tool will be used, what type of data will be captured, which sources the company will use and other related factors. Regarding the basis for capture, they can be:

  • Internal reports;
  • Performance indicators ;
  • Satisfaction surveys;
  • Business systems, including BI-oriented;
  • Customer records;

The ideal is to use varied sources, always considering the needs of the business. At this point, it is also worth doing the mapping to ensure greater control over the information captured and its destination.


The next step is to store the information. The company needs to define how and where the data will be kept, considering all devices and systems. It is quite common to opt for cloud servers, but physical servers can also be used to maintain backups and reduce the risk of data loss.

It is even worth reinforcing data security issues to ensure compliance with the LGPD and reduce any losses that improper access or damage to records can generate in internal processes.


When learning about what Big Data is, you saw that organizing data is part of the concept to be used for business development. Therefore, when implementing the strategy, it is necessary to define how they will be arranged in the system.

Commonly, they are separated between structured and unstructured to establish the type of treatment and the steps they will need to go through before reaching the final phase. You must also determine different categories, specific storage locations, access authorization levels, and other factors.


Finally, applying Big Data requires the analysis step, which means evaluating all the data collected to extract useful information and strategies for the business. In practice, this can be done in different ways. See the main types:

  • Descriptive analysis: tries to bring a view of the current moment from a history of information;
  • Predictive analytics: works with future projections from the data to try to anticipate problems and trends;
  • Diagnostic analysis: examines causes and consequences of certain actions or measures to make adjustments to the business;
  • Prescriptive analysis: aims to identify the possible effects of an operation.

Evaluating how the extracted information will be used and interpreted is necessary. At all stages, it is important to have support software and tools. Solutions such as BI, for example, become essential to take advantage of the full potential of Big Data in the company’s management.

Also Read: How to scale an AI project?

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