Comments on: Why Trifacta is teaching humans and data to work together

By: Chunting Xiang

Chunting Xiang — Mon, 29 Oct 2012 23:33:35 +0000

Great vision Doug.

By: gmconklin

gmconklin — Sat, 06 Oct 2012 00:07:10 +0000

Random-ness: I do apologize that this is a bit fragmented in terms of the complete idea… (I can provide some of my rough outline notes to potentially help clarify my position here) the kernel tuning being only one aspect, but cited to show the depth and breadth of what I am researching. So ‘self healing’ and ‘aware’ elude to complete machine learning based on a larger scope, again hence the inclusion of kernel ‘hacking.’ The kernel itself can actually lend itself nicely to self healing if in fact its ‘syslog’ output for example, were made to be a more meaningfully parse-able tool… its cryptic output should be replaced with more elegant solution possibilities, all from the kernel perspective, if that fails then it is handed to the application side to be dealt with in an algorithmic manner, as is typical for most front-end implementations of machine learning. Not sure starting from scratch is my goal with the kernel, probably more module amendment or extensions unless that proves ineffective/inefficient. The cash value from where I am coming from would be a more complete standalone solution, one that trivializes its own management by including that as part of the offering. Imagine building a base system, deploying it within your infrastructure and it can immediately survey and learn from ingestion and/or from peer nodes in place and begin/supplement the decision/remediation scope. I also see this more holistically as being a replacement for current management models, finally allowing us all to move away from the mundane (my opinion) aspects of, in some cases endless troubleshooting to root cause analysis, to making that ordeal a “non-event” category allowing us to all focus on more important things… innovation to facilitate further innovation is how I see this effort… Sure we could all still ride horses, but we don’t. Plug in to that!

By: gmconklin

gmconklin — Sat, 06 Oct 2012 00:03:13 +0000

Where is this presence in the back end of all things, the foundation of the infrastructure… I want to build that part!

By: Thomas Johansson

Thomas Johansson — Fri, 05 Oct 2012 06:25:04 +0000

This is already what the company Expertmaker is doing. I checked them at a Hackathon they had with Vodafone on information overload theme.
They already have network of thousands of users working with their desktop tools, providing data cleansing, analytics, data mining, etc. spanning over almost all types of AI (like image recognition, advanced text classification, etc.) in order to transform databases, structured or unstructured data into predictions, decision models, feature extractors, etc.

By: Doug Laney

Doug Laney — Thu, 04 Oct 2012 14:21:55 +0000

Great piece on Trifacta Derrick. Certainly a real trend and an interesting venture. And great to see the industry broadly adopting the “3Vs” of Big Data that Gartner first introduced over a dozen years ago. For future reference/attribution, here’s a link to the piece I wrote back in 2001 first defining these 3-dimensional data challenges: http://blogs.gartner.com/doug-laney/deja-vvvue-others-claiming-gartners-volume-velocity-variety-construct-for-big-data/. –Doug Laney, VP Research, Gartner, @doug_laney

By: Derrick Harris

Derrick Harris — Thu, 04 Oct 2012 13:27:48 +0000

Thanks, fixed.

By: George Balayan

George Balayan — Thu, 04 Oct 2012 12:46:25 +0000

the link to Trifacta (“called Trifacta wants to solve this”) is broken