Streaming Data in the Enterprise Hits a Tipping Point: Our 2018 Predictions
On January 18, 2018 Information Management published an article that we contributed about some of our predictions for this year in the big data and analytics space.
The key takeaway is that stream processing is maturing from technology, product, and market viewpoints. As a technology, we believe that a wide variety of future data applications will be based on today’s popular stream processing technologies. And as stream processing platforms (like dA Platform 2) are maturing and being adopted widely in the enterprise, stream processing is gaining tremendous market momentum that directly translates to business ROI.
Below is an excerpt from the article, Streaming data in the enterprise hits a tipping point, summarizing our predictions.
Data is transforming every industry, from financial services to retail to healthcare to transportation. The ability to react to data in the moment and engage in ongoing “conversations” with customers is what separates many winners and losers today.
Streaming data is the DNA of large-scale tech companies like Facebook, Google, Netflix and Uber that continuously redefine and improve businesses operations, how they engage with customers and how they maneuver the competition. The stream processing ecosystem has matured and is growing fast, and 2018 will be a watershed year for streaming in the enterprise.
Here are five predictions for what we can expect in 2018:
- Stream processing technologies will become mainstream in the enterprise by the end of 2018, moving beyond technology companies.
- Enterprises will invest in new products and tools to productionize and institutionalize data stream processing.
- Stream processing will expand beyond fast movement of data or simple analytical applications to operational applications that make true use of stateful capabilities.
- The days in which we distinguish between “batch” and “stream” data processing will soon come to an end.
- Companies will realize business ROI faster with real-time data technologies than with Hadoop.