Data engineering

Companies today produce vast amounts of data – from information about customers, value of sales, and stock prices to an assortment of internal data. Understanding what this data tells us is sometimes neither easy nor simple, so companies use data engineering to gain valuable insights from everything that happens with their business.

The company needs to design and build systems intended to receive and process immense amounts of diverse data generated at high speed by various sources and integrate it into decision support systems.

The goal is to find as many practical applications of information as possible in order to achieve faster business success.

During the implementation, we use a set of technologies that enable fast and simple horizontal scalability of all system components. This solves the bottleneck problem and addresses a wide range of challenges, starting with the sheer amount of data and ending with the need for almost instantaneous availability.

Collection, adaptation, and unified approach in the presentation of data enables development of new business models based on maximum exploitation of available information.

We primarily use tools and technologies from Cloudera data management technology package during implementation of data engineering projects. Technologies for information storage, cataloging, and advanced data exploitation are also available in the same solution ecosystem (these are, most often, advanced analytics (AI) and machine learning (ML) projects).