Big Data: what is it, and what is for?

Jorge Ignacio Gomez

Jorge Ignacio Gomez

In the digital society data grows with just one click. When a word is written in a search engine, post in social networks or just carrying the cellphone in your pocket, you’re leaving traces about who you are, what you like and what you do.

In this way, every single day we are generating 2.5 quintillion of bytes in information. This number never had such a precedent in history. In fact, according to IBM, 90% of data in the world have been generated in the last five years.

This amount of information has allowed to enhance business processes, manage risk, anticipate user behavior or even improve advertising campaigns. Basically, make effective decisions.

And all of this, has been possible thanks to big data.

What is Big Data?

 According to Gartner’s, big data are varied information assets, with high-volume and high-speed. Due to the complexity of this data, its processing requires the use of more sophisticated and innovative technologies to capture, store and simplify decision making.

Therefore, in the world of data science, the 3 Vs (volume, Velocity and Variety) are necessary for certain information to be processed using big data tools and techniques.

However, just the volume of information is insufficient by itself. It is even more important to know what to do with the data that each company collects.

Therefore, big data is more than the size of the information. It is the opportunity to answer questions about your business from data analysis.

Thus, big data has become the main material of any industry to take real actions. That’s why, companies that know what big data is and what is for have a significant advantage over other business competitors.

Despite this growing position of the data, in our Report on the adoption of digital transformation, we discover that in Latin America 42% of companies have not started or are in a very beginning stage of information management.


What is big data for?

Big data will help you make decisions about the needs of your client, have a better organization of your inventory system or release of new products and services. With big data you can analyze different data sets and find relevant information for your business:

– early identification of problems or failures in real time;

– product development according to the needs of your audience;

– risk management and fraud detection;

– forecast of market changes.

– consolidation of the relationship with the user.

This is a small list, but in real life, there are many other examples that teach us what big data is for and the enormous potential it offers to companies in different industries.

In the oil and gas sector, for example, different data collection technologies have been developed that require processing and analysis.

With the tools for acquisition of measurements while drilling (MWD) or acquisition of records while drilling (LWD), large amounts of data are transmitted to the surface in real time. In that process everything is measured: fluid pressure, temperature, formation space, extension, among other parameters. Even during oil exploration, mechanisms are used to take 3D images of the underground layers or the underlying geology.

For a human, analyzing this information in detail would become a headache, as it would take a lot of time and generate a high degree of uncertainty.

With big data, on the contrary, data processing is doing in real time, quickly and truthfully, which helps preventing possible damage or explosions in the infrastructure.

But even big data analysis can be incorporated into people’s daily life.

Through IoT (Internet of Things), by connecting an appliance to the Internet, we could collect data to identify consumption habits, device location, preventive maintenance or possible breakdowns.


What kind of data are processed with big data?

Now that you know what big data is and what it is for, you surely want to know what kind of data can be processed.

(Spoiler alert: everyone you can imagine).

Google, through big data algorithms, processes per day more than three billion searches around the world. At the same time, follows the trail of billions of websites and stores hundreds of petabytes of information.

If Google does, imagine what a small or medium business can do, especially if we consider that this is the dimension of the digital transformation with less development in this kind of companies.

According to the University of Stanford, the development of big data in the cloud allows small and medium enterprises (SMEs) to access these technologies at a lower cost, since cloud computing implies a lower complexity of development and an easier scalability.

In addition, SMEs can also use big data to simultaneously consult information from different sources, such as CRM, market analysis, ERP systems, among others, which usually have complex data structures in different formats and flows.

In addition to the data it collects about its customers, its industry or its internal organization, there are countless information that provides complete knowledge about the customer, and that companies often leave out of the analysis.

Therefore, data sources in a big data processing can (and should) be varied to take out relevant conclusions: CRM, ERP, web analytics tools, social network monitoring, monitoring systems and data acquisition (Supervisory Control And Data Acquisition – SCADA), among many others.

When we talk about variety, we mean not only those data that you store in your company’s database, but everything else.

Big data could capture and analyze structured and unstructured data, such as texts, navigation, videos, log files, etc. It can even process the data generated by a machine.

Do you know that structured and unstructured data are? Here is an express description:

Structured Data:

They are those that are stored in an organized and defined way following a defined format. They are regularly sorted in tables and stored in databases related.

Unstructured Data:

Massive and disorganized set of data, without an identifiable internal value or structure. For example, emails, text files, comments on social networks, videos, images, etc.

Where to start with big data?

You already know what big data is and what it is for, but you don’t know how to start applying it in your business? Do not worry. Click on the link below, download our free e-book and discover what you need to get started in the world of big data.



Jorge Ignacio Gomez

Jorge Ignacio Gomez

Information technology specialist with more than 20 years of experience in operation, engineering, architecture, data center, networks, security, Cloud, marketing and sales, leading teams and transversally for innovation and digital transformation of businesses. I contribute to society through teaching IT, Security, Cloud and Datacenter.