Anomaly Detection

One of the key advantages of machine learning is the ability to quickly look at large volumes of data and identify transactions and other events that don’t fit the expected patterns. That’s important for more than only network management. Fraud detection, advertising effectiveness and other analysis benefit from anomaly detection. My latest forbes.com column discusses the basics.

My Artificial Intelligence and Machine Learning Year in Review Post is up on Forbes.com

My annual (I’ve done it twice now, so that now fits) has been posted. I review some of the key stories I covered in 2018 and make some basic predictions for what will happen in the near-term future. Hint: Aritifical intelligence and machine learning are still early in the adoption lifecycle, but cloud technologies mean faster adoption curves than in the past.

SAP looks at blockchain and other options for distributed ledgers

While at SAP TechEd in October, I talked with people about artificial intelligence and other leading technologies. One conversation took me out of my core zone and into how the company is looking at blockchain and other ways of providing distributed ledgers. My latest Search Data Management article discusses what I learned.

ThoughtSpot Announces SearchIQ

ThoughSpot is an analytics company and they made a number of announcements at their conference this week. One that caught my eye was about SearchIQ, a new product for natural language processing (NLP). It layers text and voice query on top of their platform. Read more in my latest article on forbes.com.

Deep learning algorithms, and a short comment about SAP and Cloud

A couple of new articles over on the article page.

The first it almost a counter argument to the data problem I’ve previously discussed. It’s not enough to have good data if people can’t trust the algorithm.

Then, at SAP TechEd 2018, Bernd, Leukert’s keynote speech had one key element that showed me that the company was finally internalizing the ecosystem focus needed to thrive in the cloud versus the on-premises model they’ve used for decades.