What you missed in Big Data: Vertical-specific knowledge
The analytics ecosystem became even more crowded last week after Hitachi Ltd. tossed its hat into the ring with the introduction of new data services aimed at addressing the highly specialized needs of vertical segments. The launch marks the first fruit of its nine-figure acquisition of Pentaho Corp. this year.
The generic business intelligence capabilities that the Japanese industrial giant gained through the deal are now being applied to niche problems in the most strategic areas in which its primary infrastructure and manufacturing businesses operate. One of the new services promises to help medical professionals find useful patterns in patient information, while another offers to provide visualization capabilities to help public safety officials make sense of data from sensors and cameras.
That’s the same type of specialized use case that Clarifai, Inc. is targeting with its emerging computer vision technology, which uses a unique homegrown concoction of algorithms to parse visual input much faster – and thus cheaper – than a human. The software landed the startup $10 million in funding on the same day as Hitachi’s announcement, with investors including the venture capital arms of Google, Qualcomm, Inc. and Nvidia Corp.
But although computer vision currently only has narrow applications in a number of niche fields, the ability to automate the process of distilling raw data into insights is emerging as a powerful tool across the entire enterprise, even for the most routine everyday operations. That’s what earned Rocana, Inc. $15.5 million in its own funding round from Google Ventures barely two days after Clarifai.
The startup will use the new capital to pay for more developers to work on its namesake monitoring service, which scans logs from different parts of an organization’s infrastructure to assemble a complete picture of components and processes. That visibility can come in especially handy when something goes wrong and administrators need to find the root of the problem, particularly in large enterprise environments with upwards of hundreds of workloads scattered across multiple locations.
Image via Pixabay
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