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Big Data


Analyze terabytes of data in a distibuted environment.
Process streams, deploy Machine Learning models on clusters.

What is it?


The big data has become a buzzword in recent years and has been surrounded by many myths. In fact, it is an umbrella term for a set of technologies and, above all, the methodology of how to store, transmit, analyze and draw conclusions from the amount of data that individual machines cannot cope with. Morover, Big data systems have built-in fault tolerance, which makes data loss much less likely.

Is my company in need of Big Data technologies?


Nowadays big data is closer than you think. Not only tech giants like Google or Facebook generate large amounts of data. A company that generates as little as 3 GB of data per day for a year will already have a terabyte of it. Some data can be deleted, other is valuable knowledge, for example: customer behavior on our website or measurements made by IoT sensors. They help you to have a better insight into your business and to predict its behavior in the future.

Big Data Technology


Thanks to solutions such as Hadoop or Spark it is possible to store and create analyses based on large data sets. Tools such as Elasticsearch allow to search millions of text documents very quickly. And Kafka provides us with the ability to collect information from thousands of devices simultaneously. Similar functionality can also be provided by tools made available within public clouds such as AWS.



Thanks to this, the projects consisting in the oscillation of the entire hall, real-time detection of anomalies such as changing the characteristics of electric motors (indicating, for example, a failure), creating models that allow for the premature replacement of devices whose service life is on the finish while providing the possibility of quick manual access to the necessary information is not a science-fiction concept.