Teradata

If you see, when organizations started on this journey of data and AI, they used to be on MPPs, and then Hadoop ecosystems took play, and then data lakes sprawled.

And when cloud came, there was a migration from MPPs, whether it is a Teradata, Exadata, or whatever, and Hadoop ecosystems onto cloud.

The whole thought process in terms of data architecture, data modeling lost its glory.

And as a result, what happened was when enterprises realized that, hey, AI is the new ways of working, people have suddenly realized that the whole concept of data modeling, data modeling from the perspective of governance, from the perspective of having domains created, lost its significance.

Deloitte puts the pilot to production failure rate at eighty-nine percent.

Teradata finds seventy-eight percent of enterprises running pilots, but only fourteen percent scaled organization wide.

And Gartner counts just one hundred and twenty of one thousand budgeted initiatives reaching production.

The named culprits are specific.

It, it's, um...

You know the old Teradata boxes that were like Christmas trees when the lights went up, when, uh, all the different nodes were, were sparking, and now we run queries? Uh, we don't see the lights anymore, uh, uh, but similar things are happening.

And I think it's, uh, it's a lot of it also has to do with, uh, us as humans, you know, asking the right questions, and we don't always necessarily...

If we don't quite have the context right when we ask the question, um, you know, it, it's hard to convert that into a query or a dashboard or something like that and, and get the answer this way.

So I got to see what a lot of companies were doing in a lot of different kinds of industries.

You know, for several years, I was chief analytics officer at Teradata.

Back in its heyday, also a small research advisory firm called International Institute for Analytics, which was founded by Tom Davenport.

We focused a lot on ethics there.

It's a tooling constraint.

During my career, I've seen it from the Teradata movement to the big data era, so you move from Teradata to Hortonworks and Cloudera on-prem.

A few years later, you then say, actually, what we need to do is then migrate to a cloud provider, so go from on-prem, big data platform to the GCP and AWS and Azure.

What I have seen and what really has kind of stayed with me is just the observation that you change your platform but a lot of the problems don't go away and that's really because it's too easy to focus and blame the challenges around tooling.

Deals were getting bigger.

And when you and I met, I had been at Teradata for, well, it was like my second year.

I had... gotten close to my quota right i'd gotten 90 i think it was i had um closed the biggest deal of my career so far i had made the most money of my career that previous year you know i was feeling pretty good about myself And about where I was going.

But when I met you, it was a pretty stark difference between the sales leaders I had worked for before.

We were able to point to this outage, which was a horrible thing and it was a bummer that it happened.

But we were able to point to that and say, this actually wouldn't have happened if we had already done what we're asking you to do.

And that outage, because it escalated up to the CIO, because it was such a big deal, the answer for what should we do to make sure this doesn't happen again wasn't like get away from Teradata.

It was we should make these investments with Teradata.