The value of real time data stream processing for the enterprise

From TfL to Netflix, stream processing provides faster insights for data-rich businesses

Using data as an analytical tool can be incredibly effective. However, a data rich company is not necessarily a successful company. Today, it is critical to evaluate data and respond to it in real time, in order to be competitive and to make effective business decisions.

This is where stream processing and real time data analytics, comes in. Although insights derived from data are useful, the value of some events rapidly decrease as they age.

As a result, open source data stream processing platforms are increasingly gaining traction in the world of data management. Real time data stream processing can efficiently handle massive streams of events in motion and provide data insights within milliseconds.

Initiated by the founders of the aptly named company data Artisans, the Apache Flink ® open source platform framework addresses the inherent challenges of stream processing and real time data analytics. Over the last years, Apache Flink established itself as one of the most competitive open source stream processing engines.

One of the integral elements of digital transformation is big data. It entails larger, more complex and constantly growing data sets that exceed the limitations of traditional data processing software.

The value of data is indisputable, and insurance investments in big data are forecasted to soar to $2.4 billion this year alone. To truly harness the power of big data, however, companies must process the volume, velocity, and variety of big data in a timely and meaningful manner.

Investment in big data therefore demands investment in data processing. Companies are only able to reap the benefits of data collections if they are able to efficiently run and easily understand their analytics, ideally in real time as the value of results quickly decays.

Data visualisation can transform complex data sets into incredible visual insights, while stream processing manages data in motion. Combining both batch and stream processing can enable companies to transform their data sets into invaluable business insights.

“We have seen real traction for stream processing, data movement and of course data management in open source,” Donald Farmer, principal at consulting firm TreeHive Strategy said. “One important exception has been open source data visualisation, a critical component of analytics,” he added.

Stream processing enables users to effectively manage a continuous data stream. From Uber to Transport for London, stream processing allows the world’s biggest businesses to process data in powerful ways.

The prestigious Apache Flink® conference, facilitated by data Artisans, takes place September 3rd-5th 2018 in Berlin, with companies such as Alibaba, ING, Netflix, Airbnb, Uber and more sharing their latest use cases. Register for Flink Forward here.