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I've taken my eye off the analytics news of late. Prepping for that pesky ARC Forum just took up so much time! (Seriously, the forum turned out to be a lot of fun actually, hope you were there....). So to get caught up I've hand-picked a few interesting stories for you:
- Machine learning is coming to industry, so pick wisely: One of my sessions at the forum last week focused on machine learning. (I'll reprise that session in a blog post in a week or two). We clearly saw the growing importance of ML, with vendors like RailComm and Flowserve talking about how machine learning is embedded in their infrastructure monitoring and maintenance solutions. Generally, I think there are 3 paths to machine learning. I think very few industrial companies will build their own machine learning applications. Sure a few will - the barriers to building machine learning applications have never been lower (as I wrote in my machine learning strategy report). Many more will adopt applications that incorporate machine learning - some of them without even knowing (or caring) about that. But as this article (Is the road to machine learning paved with API providers?) suggests, there is a third way, a middle ground. That is to piece together your own app using services provided via an API (often called micro services). As the article describes, you can find these services at IBM Watson, Microsoft Cortana and Algorithmia, which takes an independent marketplace approach. There are many other service providers emerging too.
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Microsoft Releases the Azure IoT Hub to General Availability. Not analytics per se, but very relevant to enterprise industrial IoT platforms. The addition of the Azure IoT Hub is one example of how enterprise software vendors will need to build back towards device connectivity - either through build-out, strategic partnerships, or outright acquisition. Without some footprint in most areas, I think IIoT platform vendors will struggle for traction.
- A ripple on the road to visual data discovery. The visual data discovery market got a little shaken up while I was looking the other way. (Quick disclaimer: Don't use anything I write here as investment advice). Tableau's stock price took a severe beating because it reduced it's forecast a bit - not a huge bit, just a bit. Balance that out with Qlik (a Tableau competitor) posting good revenue growth, albeit from a more mature market position. Overall, there is stacks of growth left in the visual data discovery market, we've barely even started. But, as I noted a couple of years ago, every mature BI vendor now has a "me-too" Tableau clone. So, there is going to be a headwind. Some deals may not materialize for pure-play visual data discovery vendors - using the incumbents clone will be deemed good enough. In other cases, the sales cycle may simply get longer.
- The rise of open data. We've all been excited about the value of open source for years. (We have, haven't we....?). Starting with RedHat, there are now open source options for pretty much any class of enterprise software that you care to think about. So let's talk about open data instead. Open data is simply data that is freely available to the public. We're becoming awash with data. But, that doesn't always mean that we have the right data. Open data sets can be a great way to supplement corporate data for the right projects. Bernard Marr has put together a good, but surely not exhaustive, list here.
- Finally, I don't often link to press releases because....well, because they're press releases basically. I've written a few in my time, and read thousands more - they can be a little lacking in detail, and a little too full of bull. This one is not so much. I include it as it illustrates an emerging need that I frequently write and speak about: The need to move industrial analytics and operational intelligence closer to real-time. In this example, EDF Renewable Energy was able to do that with OSIsoft, SAP HANA, and some help from KPIT.