For a long time, discussions about big data have centered around its technical aspects but now the focus has switched to actual usage scenarios.
Nevertheless, the technologies and tools companies use for big data is still highly relevant. Big data analysis is often only possible in combination with new technologies and tools or ones that haven’t received much attention in the past.
The current market for these technologies is highly dynamic and many big data tools promise a broad spectrum of benefits. But which technologies have made their way into organizations, and which ones are on the radar for the future?
The three technologies most commonly used today for big data are all standard technologies.
Organizations often use standard BI tools and relational databases, underlining the importance of structured data in a big data context. It is also apparent that big data tools will not simply replace standard BI tools, which will continue to play a significant role in the future.
The challenges that coincide with big data initiatives, however, show that companies will increasingly extend standard tools with specialized technologies in the future.
In fact, technologies that increase the usability of poly-structured data (e.g., Hadoop ecosystems, NoSQL databases), enhance the speed of analysis (streaming systems) or enable better forecasts (predictive analytics solutions) have the highest rankings for planned investments.
The growing number of big data use cases and the adoption of new technologies go hand in hand. As a result, companies will soon face even more heterogeneous IT landscapes, which will create further challenges.