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It's a quick roundup this week, with a handful of stories in that sweet, sweet intersection of the Industrial Internet of Things and analytics:
- How big data is changing the database landscape for good. Or, in our case, we can cheerfully substitute Industrial IoT data for big data. This article drops in a couple of brief real-world case studies and a few vendors that can help to broaden your understanding of the good and bad about NoSQL. Also, Andrew Oliver's guide ti databases that is referenced there is a more expansive read for those with more than a casual interest.
- Oil company hopes to strike efficiency with cloud analytics. O&G, cloud and analytics are 3 terms that you don't often see together (yet). Tidemark is a company that I was introduced to at Aberdeen, but had lost track of (resisting a bad pun here...). Frankly, Tidemark is more forecasting and planning, but I do remember it had a nice clean interface and fresh approach - strong on collaboration and mobile.
- Cloud-based ‘Deep’ Learning Tool Explains Predictions. Rice Analytics is a company that is new to me. Honestly, I'm not sure how ready it is for commercial prime-time, just based on its website. But, IIoT data means we are sorely in need to advanced analytics solutions that truly provide context to decision making. So, this might just be worth checking out...
- Machine learning is still a very lively space at the moment. About a week ago Google announced that it would open sources some of its machine learning algorithms as something called TensorFlow. Here are the reason's why Google did that. Not to be outdone, Microsoft announced something similar this week. And - just to prove how hot machine learning is - even The Economist is writing about it.