Big Data & Data Science

We know how.

To use big data effectively requires new and innovative forms of information processing, including unconventional data management technologies, architectures and analytical functions. The potential application scenarios for big data are meanwhile both extremely comprehensive and very individual. But regardless of the particular use case, the same implementation challenges arise time and time again. It always comes down to finding a way to efficiently handle large data sets, quickly process the data streams, and master complex analyses. That is why we have developed implementation solutions for big data projects which address these three challenges.


  • Store & process very large data sets
  • Capture & process fast data streams
  • Advanced Analytics & Data Lab

“Trivadis masters in equal measure both traditional and new big data technologies, as well as complex analytics. That is the telling advantage.”

Big Data Canvas

We take the Big Data Canvas architecture approach to create the full scope of a big data solution using seven coarse-grained architecture modules. Each of these building blocks forms a functional area for processing analytical information, which is initially broken down by fine-grained architecture building blocks, before being finally stored by the corresponding solution components, so-called solution building blocks. This approach allows the realization of highly standardized and integrated big data architectures to accommodate every individual business case.

  • Standardized architecture
  • Proven solution components
  • Investment security

trivadis big data science

Trivadis, Peter Welker, Senior Principal Consultant

Peter Welker

Trivadis, Senior Principal Consultant