What is big data?

Created in:
Sep 9, 2021

Understanding the essence of big data and the ways to analyze it are essential for companies to know how to deal with the challenges of today's data-driven market.

So, if you want to know how to update your business and ensure your success in this data-driven future, read on.

You will understand what big data is, learn about its history and learn how it works in practice. Follow!

Big data concept

Big data refers to an immense volume of data that cannot be processed by databases or traditional processing applications because it is generated at high speed and great variety.

Every day, 2.5 quintillion bytes of data are generated, and it's modern big data solutions that enable the analysis and interpretation of it all.

Today, we have several big data tools available to the market, which are of great importance in defining business strategies. With them, modern companies have the opportunity to improve their results on scales never before imagined, from:

  • process optimization
  • increase in productivity
  • of the highest growth rate.
  • reduction of various costs.
  • smarter decision-making.

These and other benefits have made day-to-day business safer and more efficient.

But how did big data come about?

Big data: once upon a time...

Although the term big data was only disseminated in 2005 by Roger Mougalas, the search for understanding the available data and its application has been around for a long time.

In fact, some of the earliest records of the application of data to analyze and control business activities date back more than 7,000 years.

That's it!

It all started in Mesopotamian times when, in order to facilitate the recording of crop growth and grazing, accounting began to be introduced into the daily lives of traders.

Much later, in 1663, we had the first statistical analysis of data ever recorded. In order to raise awareness of the effects of the bubonic plague that was ongoing at the time, John Graunt recorded and analyzed the death rate in London and, for these reasons, is considered a pioneer in the field of statistics.

After Graunt's contribution, the principles of using data continued to develop. For example, in 1889, in an attempt to organize census data, Herman Hollerith created a computer system.

But after that, nothing very extraordinary happened in the area until the 20th century, when what we call the information age began.

So the starting point of data as we know it begins in 1937, when the U.S. Congress passed the Social Security Act and hired IBM to develop a system for this broad data project.

Then, to crack the Nazi codes in World War II, in 1943, the first data-processing machine, Colossus, was developed by the British.

And since this development, the use of data and machines has only evolved. Whether for military, accounting, or other purposes, these technologies made life and business considerably easier by collecting and processing information independently and automatically.

And so the 21st century began.

Ten years after the first supercomputer was built, in 1995, the world was first introduced to the term big data, by Roger Mougalas, director of market research at O'Reilly Media.

And it was also in that same year (2005) that the company Yahoo created the (now) open source Hadoop with the intention of indexing the entire World Wide Web (www). Today, Hadoop is used by millions of companies to analyze immense amounts of data. From then on, the amount and variety of data increased rapidly, especially with the growth of social networks.

Today, companies and governments have started to establish constant big data projects to make their decisions, and even people use this powerful resource in their daily lives.

How does big data work?

Big data analytics is the process of finding patterns, trends, and relationships in large data sets, compiling them, processing them, and analyzing them to aid in decision-making.

The main objective is always to generate value for the organization and, for this, specific tools and techniques are used for each business.

And how does this happen in practice?

The first step in the process, before implementing any technique or tool, is to make a study on the characteristics of each company's data and analytics, based on the 5 Vs of big data. They are:

  1. Volume: Size of the data (petabyte, exabyte, zettabyte).
  2. Variety: Data format (tables, images, texts).
  3. Speed: How quickly data is generated (per second, per minute).
  4. Veracity: reliability of data (sources, integrations, communication).
  5. Value: Outcomes that data brings to the business (context, problem, solution).

Then, after identifying the data and the challenges to be overcome by the company, large-scale data processing systems and scalable data distribution system architectures can be built to be used in the projects.

Here are 2 practical examples of using big data

Here at Indicium, every day customers come looking for big data and data science solutions to overcome their business challenges. Let's get to know some of them?

1) How Indicium helped a business consulting firm visualize data from over 40 million companies in an interactive and efficient way

Once, a client came to us wanting to perform big data analytical queries and make decisions based on information about their segment in the Brazilian market.

To this end, our team was challenged to collect all statistical data from the IBGE and public information from more than 40 million Brazilian companies available on various portals and websites of the federal government.

As a solution, we implemented and automated a crawler structure on all government websites, as well as storing this information in a database in the cloud.

Do you know what the results were?

This large volume of information was organized into a customized dashboard and transformed into intuitive visualizations that offered an advanced market intelligence experience for the customer.

As a result, you have saved a lot of time that was previously dedicated to research and can focus on improving your service and increasing your sales.

2) How Indicium helped the largest real estate company in Santa Catarina visualize information and gain insights from data

In order to make better decisions in the marketing area, a large real estate company came to us with the purpose of being able to visualize, in one place, its internal big data.

In this project, we were challenged to create a robust and fully customized business intelligence strategy, using data from the marketing, CRM and ERP areas, with the help of the Power BI tool.

How did we do it?

We started by importing the data from the various sources available, and then we developed a data warehouse and a data lake, so that we have a solid database structure in the cloud. Then, we create a fully customized dashboard that is updated with Power BI.

As a result, the client is being able to create strategies for capturing real estate and make data-driven financial decisions.

Invest in big data

Here at Indicium, we use the best and most advanced big data tools available on the market, in addition to having a team of experts in the field.

Do you want to implement big data solutions into your business strategy? Get in touch today and get help from our team.

Big data

Bianca Santos


Keep up to date with what's happening at Indicium by following our networks:

Prepare the way for your organization to lead the market for decades to come. Get in touch.

Click on the button, fill in the form and our team will contact you shortly.

We want to help you with your data initiatives.