The volumes of data being created today are staggering – every device with a sensor, a radio, a signal, a connection of some sort is perpetually creating data, much of which can be used to deliver experiences, products, and services to users or customers. It really started with the precipitous drop in storage costs, driving the world of big data and analytics to new heights. But, we live in a real-time world, largely driven by a consumer-driven instant gratification mentality, where content is driven instantly to devices. Whether it’s seeing real-time social media posts, instant sports updates, online auction feeds, or dynamic weather or traffic information, consumers no longer are willing to wait.
Those same consumers, however, are also employees, analysts, and executives, but the business world, as it often does, lags behind consumer trends (think about where the mobile device phenomenon began). Ultimately, though, the question became: Why can’t we have access to real-time business information as well?
That’s why Steve Wilkes, co-founder and CTO of Striim, along with his partners, saw an opportunity to enable real-time business insights, which could help businesses create differentiation and drive business innovation using live, real-time data to drive decisions and actions. They came together in 2011 and created Striim, a real-time data integration and streaming analytics software platform.
In a nutshell, Striim allows businesses to collect and analyze real-time data and turn it into actionable intelligence – whether automated or human activity – without incurring the inherent delays in post-storage processing. In fact, Wilkes notes that for many businesses, which may be dealing with hundreds of thousands of events per second, storage is simply not possible. When you consider the real-time nature of much of the analytics that take place today, especially around location-driven analytics, data value has a finite, and often very short, useful lifespan.
“We are literally producing more data than can ever be stored, between 3 and 15 percent, depending you who you talk to, can ever be stored,” Wilkes says. “In addition, latency goes up massively when you store data, and some data is perishable. When you move into the real-time space, data doesn’t just lose value over time, it drops to zero very quickly.”
One example he cited, which many of us can relate to, is the crowdsourced navigation app Waze. That has the ability to dynamically reroute drivers in real time based on changes in traffic patterns and incidents.
“Imagine sitting in traffic for several hours, then getting home and receiving an email or alert telling you there was an accident three hours ago and to try a different route,” he says. “That’s not very useful.”
What Striim is enabling through general purpose middleware is the ability to build out data flows that do anything from simple real-time data integration, to complex collection, pre-processing and processing, filtering, aggregation, redundancy removal, analytics, and scoring. All of that can be done either at the network edge, on premises, or in the cloud, depending on varying business needs – or in all three places, which Wilkes says Striim is doing with Microsoft (News - Alert) for Industrial IoT applications.
Striim has been built to be scalable and to handle the most massive data streams. But what’s most important, Wilkes says, is not so much the volume of data, but the requirements of getting instant insight from the data, with an eye on the data depreciation rate.
Working with customers in various industries, including health care, airports, financial institutions, telecom, IoT, and cyber security, Striim allows data to be collected from multiple sources, joined, and analyzed to drive real-time business decisions.
“We see data coming from change data in enterprise databases, but a lot of it is real-time data collected within enterprise environments,” he says. “The insight has become more important than the volume, and we saw a need for a platform that would do everything end-to-end – the real-time collection, processing, delivery, visualization – that was our goal when we started the company, and that is what we have achieved.”
Whether it’s simple data integration, adding analysis and trigger detection, or even monitoring and visualizing real-time metrics, Striim enables businesses to leverage data from any number of sources, parse the data, and export actionable intelligence to drive action in real time.
In cyber security, for instance, he points out that there are countless solutions already available, but often attacks or exploits aren’t visible from a single log. As attacks become more complex, the ability to correlate data across multiple logs becomes critical to threat detection.
In today’s real-time, agile business environments, the ability to leverage streaming data to produce productive business insights is not only much more efficient than the traditional batch processing methods, but can create differentiation in competitive markets that delivers real business value. In a streaming world, streaming data only makes sense.
Edited by Alicia Young