PREAMBLE:  

This video was built as a result of our internal hackathon using Teradata Listener to absorb real time small messages from Transformers and other devices on the Power Grid in Southern California. The video demonstrates a real time predictive analytic showcasing proactive repairs of the power grid to reduce costs and avoid disruptions of power service.…

Please watch my new video on Aster on Hadoop and get a simple demonstration of how easy it is to perform advanced analytics with Hadoop data!

This announcement is a very exciting prospect for some but may strike fear into others. In my blog, I will entertain some of the interesting prospects of bringing together these technologies. I also hope to allay some fears as well.

One of the biggest announcements at Teradata Partners 2015 is that Aster will run on Hadoop. Many of our customers have already…

In part one of this blog post we discussed the traits of people you should try to build in a data science team.  Of course technical, statistical, programming and mathematical skills are needed.  However, it takes much more.  We discussed the following traits:  The Pioneer, The Cattle Herder, The Muscle, and The Story Teller.  See below for that blog post:

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Writing SQL-MR and SQL-GR statements is made much easier by a tool I wrote while on vacation.  As an Aster Data Scientist I needed a tool that would enable me to focus on the 'WHAT' and not the 'HOW!'  I needed a tool to write the code for me.   So I wrote Aster Tango.

Please see the following list of videos that I have created to document some of Asters 120+ Analytic Functions:

Please watch this video and learn how we take multiple channels of data:  Bank systems, IVR, Call Center Notes, Clickstream, and others to perform behavioral churn prediction.  We do this at data scale and not using samples.

Please watch my video on Aster's principal component analysis or PCA. I not only show how Aster performs this analytic but I attempt to explain how PCA works and explain eigenvectors and eigenvalues. Genre: Statistical Analysis (Unsupervised Learning) Background: A process used to emphasize variability and bring out strong patterns in a dataset. This variability is expressed by principal components; which are directions of highest degree of variance. The first several principal components…

I was deep into a presentation at a major retailer. In the darkened room, a lone hand shot up. “John, we spend 80% of our time on data load and prep. Only 20% is used to produce analytics. We don’t like that ratio.”

The speaker was right. About 80% of the analytics process is spent on data preparation and loading. Numerous examples come to mind. I remember a project for an auto insurance company using telematics and driver behavior. The one-off code to prepare the data took three days…

Your website’s search capabilities may be a potential customer’s first (or only) interaction with your website.  Customers who can’t find relevant products based how they search are likely to  abandon and go to competitor websites.  For many retailers, 30% - 40% of search queries are under-performing.  Underperforming search queries are costing you sales and customers.

Some examples of under performing search queries are:

• Queries that return zero…