Big Data does not mean high costs

February 21, 2019

Our CEO Alex gave Techerati a interview about Big Data and why Enterprise customer mostly struggle to use newest technology in their IT landscape. Here some remarks, read the full article online.

Different strokes for different folks

The pro for Hadoop is the nearly unlimited scalability with an affordable price for hardware. A negative is, however, is high operational cost. Although this can be negated by using commercial distributions for an additional price.

The same counts for Kafka, Spark or Flink. That’s why modern tech giants always operate the largest installations in their own data centres, but enterprises often struggle to attract talent to get that scale into stable productions. In short − it’s great to have the tools on premise, but to operate them can be challenging.

Data-driven opportunities

Big data does not mean heavy operation costs and long-running training cycles. Nowadays it means more to understand business processes and to transform them into data-driven opportunities, using cloud technology when needed to develop your own solutions.

But using data has strong ethical consequences. I’m not a fan of storing every bit of personalised data just to have it. Clearly divide between machine and robotics data from assets, circuits, transformers, windmills, solar farms, engines, cars and so on and personal data from customer solutions to build different approaches for data analysis. Personal data belongs to the individual, and it needs to get it processed there − edge computing brings a lot of advantages to achieve this. Always stay upfront, improve and drive the digital change.