The range of potential applications for analytics in the enterprise grew even wider last week after SnapLogic Inc. rolled out a new pipelining capability that extends the reach of its integration service beyond the corporate back-end to the connected universe. The addition promises to help organizations automate the collection of data from the multitutes of new devices entering the network.

While theoretically possible, manually hooking up every end-point to the appropriate analytic processes requires more resources than the average enterprise cares to expend and makes it unfeasible to keep up with the rapid evolution of technology, a headache that the new feature removes. Developers can now create custom connectors for each use case without the burden of having to adapt the code for every major new advance that comes along on their own.

That significantly reduces the barrier to tapping into the connected universe on an organizational scale, but collecting the data coming off the new breeds of new devices emerging today is only the first step toward gaining useful insights. The real challenge is in extracting that knowledge, which is where SnapLogic hands over the torch to startups such as Nervana Systems Inc. competing further along the analytics lifecycle.

The outfit also made headlines last week after open-sourcing the code for its Neon deep learning software, which is touted as several times faster than many of the more popular alternatives. Since the whole purpose of the technology is to speed up the ingestion of data such as transmissions from a large number of connected devices that would take far too long for a human to process, that represents a leap forward.

The likes of Nervana and SnapLogic are successfully carving out a niche for themselves in different areas of the analytics process, but Banjo Inc. has proven that there is a potentially even bigger opportunity in addressing the whole. The startup raised a massive $100 million in funding against the backdrop of Neon hitting the public domain to drive the adoption of its namesake platform, which provides a unified environment for collecting and analyzing data from different parts of the digital universe in near real-time.
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