Skip to main content

Big Data


Large volumes of data treated with the best technologies.

Real-time analytics to save time and money in the management of the company.

What does it consist of?

What does it consist of?

We talk about Big Data when it is necessary to go beyond traditional Business Intelligence because the management of large amounts of information, structured and unstructured, internal and external, requires more powerful and scalable storage and processing technologies.

How I use it?

How I use it?

We evolve a Central Data Warehouse to a Data Lake, prioritizing ingestion speeds and data processing to show high value analytical results. We provide you with the latest scalable and flexible Cloud technologies.


What benefits do I get?

What benefits do I get?

A lot of possible benefits, depending on the application and applied approach. Knowing customers better than themselves, developing new products and services, analyzing risks, adjusting business processes in real time, reducing maintenance costs, knowing the whole company globally, etc.

Our services

BIG DATA strategy

We analyze your needs to guide you in the implementation of a practical and result-oriented BIG DATA architecture. We design with you a robust architecture capable of managing the volume, speed, variety and accuracy of your data. We define the strategy to use an infrastructure that stores and performs the necessary data processing to perform BIG DATA analytics.

BIG DATA infrastructure

We select the most appropriate cloud provider and define the servers and communications tailored to your needs. Criteria such as availability and scalability are priorities, in addition to budget and facility for long-term maintenance. We work with the leading vendors, with whom we plan an IN & OUT data integration, as well as the maximum use of storage and processing resources.

BIG DATA processing

The diversity of data sources and their volume are the main problems to be addressed from the beginning in a BIG DATA strategy. We bring you our experience in data processing to perform all the steps, from obtaining the data (batch or realtime) to its final usage, through cleaning, filtration and historical storage and optimized in a Data Lake. We use state-of-the-art technology and we also have our own software to perform the considered key actions of the value chain.

BIG DATA analytics

Mathematical algorithms and statistical methods allow the analysis of data and produce valuable information for the business. To answer what to do with the data, we jointly develop these algorithms and methods to suit your needs. These analyzes capable of working with data of diverse nature (numerical, textual, audio, video, images) are based on fields such as data mining, automatic learning, time series analysis or operational research.

On exponential advancement in processing and storage

Decoding the human genome took 10 years to process; now it can be achieved in a week

Facebook generates 10TB of daily data, Twitter generates 7TB of daily data, 90% of today's stored data was generated in the last two years

Our recommendation in 7 key ideas

Start from the requirements
Explore the entire BIG DATA ecosystem
Start small and then grow
Be nimble
Architect for change
Hire external experts
But focus on developing skills

The 3 steps of BIG DATA Analytics

1. Descriptive analytics

Analysis of historical data collections, visualizing them in a way that can help to understand the current and past state of the business. It tells us how the business has worked so far and allows you to detect produced but not known facts, visualize the evolution of business metrics, identify problems or calculate KPIs that summarize the state of the business.

2. Predictive analytics

Using predictive tools we can estimate unknown data, uncertain data or data that require manual processing to be obtained. The results allow to improve the business decisions and allow for example to anticipate to customer needs, detection of fraud, to discover homogenous groupings of clients, etc.

For this purpose we use statistical models which add estimated data to the already known data. Some of the techniques used are Automatic Classification of Information, Prediction by Mathematical Regression, and Segmentation of Hidden Interest Groups.

3. Prescriptive analysis

It assumes the highest level of analytics and exploits the previous levels along with operational optimization strategies to tell us which business actions will provide the best results. Through the prescriptive analysis we can obtain automated recommendations on the ideal moment to execute orders, maintenance, or other quantifiable business operations. With prescriptive analytics we can know what we must do to optimize our business.

We call you

Just leave us your data and we will contact you shortly.

State-of-the-art technology