Greater agility in production and cost reduction

Big Data in Industry

Large industries are increasingly interested in the processing power found in a Big Data environment. This ability to handle large volumes of data generated by sensors and processors enables large industries to monitor their production line efficiently and in real time. In this way, it is possible to reduce energy costs, improve production time and, consequently, increase profits.

Even small businesses can have these benefits:

  • Big data is cheaper than other systems and the storage cost is low
  • Analysis tools are increasingly sophisticated and often free
  • In an environment with a tight profit margin, each screw turn counts.

Practical examples


Seeking excellence in the quality of its products, large companies seek to replace humans with robotics. In this way, complex assemblies generate fewer errors. These machines are full of sensors, from which data is transmitted constantly.

When properly analyzed by data scientists, this information can be used to:

  • Create predictive models of equipment failure
  • Simplify Inventory Management
  • Identify Inefficient Components


IoT is a concept that is increasingly becoming a reality. RFID sensors and tags are becoming an integral part of manufactured objects, capable of transmitting data between themselves and to various other devices.

Some examples of the use of IoT are:

  • Performance monitoring of industrial equipment;
  • Control of energy consumption;
  • and many others.


Much of the data generated within an industry is contained in a structured environment and still faces a number of challenges.

  • Variety: Much important information is often restricted and each department ends up creating its own data repository. This means that data is not being shared across departments.
  • Volume: Data from human sources (vendors, suppliers, distributors, customers, etc.) and sensor networks (inside and outside the factory) grow exponentially and demand more and more computing power.
  • Speed: Production lines and supply chains quickly change structure and flow. The more dynamic the data, the harder it is to analyze them.

These challenges are easily overcome with a well-structured Big Data environment. In addition, using analysis tools, it is possible to identify correlations and patterns that are often not easily perceived.

To help your business leverage its business, Semantix's team has a number of trained experts to implement a complete Big Data solution from Infrastructure, Data Ingestion to Real-Time Analytics with complex Machine Learning algorithms.