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Trends in 2016: The next big things in the data world (Part 1) – Data Science on scale

Adding Value to Volume, Variety & Velocity

“Big data? Right on trend” – or maybe “right on trend… soon”. Whether it’s a topic to focus on or a business necessity, the targeted use of data plays a role in most companies. So now things can really take off, right? Yes, but in a different, better or more modern way than conventionally thought. We believe 2016 offers significantly more possibilities, so what are they and where will they take us? All is revealed in our small series of blog posts. Let’s start with...

Data science on scale

During the last few years, almost all large and medium-sized companies have built their own big data platforms and created and filled their own data pools. In the best case scenarios, they’ve even managed to successfully realize their first pilot projects – generating and accumulating large quantities of data from various sources before analyzing them quickly and applying statistical processes to gain new understanding.

The next vital step is to achieve financial gain, too – and on a long-term scale. Companies have pumped a lot of money into infrastructure, and now it’s time to see the business value in their investments. The need for concepts and the development of valuable data and analytics applications is growing at a rapid pace. Similarly, the demand for expertise in the field of data science and good data scientists – using mostly Hadoop-based or NoSQL-based architectures – will increase exponentially throughout 2016.

So the targeted use of data was a good start. However, despite all its effectiveness, on its own it leads us down a one-way street. To find out why, read the second part of Trends in 2016: Machine learning / Deep Learning (as a Service).


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