Hoodies and more in a generous range of sizes and colors. With old customers and new ones at different stages in their use of enterprise data and cloud adoption, he has to appear in more than one timeline and still make sense.Lake Life SVG Love You To The Lake and Back Lake SVG Lake House Decor Summer SVG One data warehousing expert told The Reg the industry likens Brobst to Back to the Future's Doc Brown. But I think there is a way to help organizations, especially in verticals like financial services or telcos, get a better handle on what the ecosystem should look like." That's harder for them to compete with some of the newer players in the market. "It would be tech startups without tech debt. "Teradata has a lot of the traditional big companies in the world as clients, so there is not much greenfield in that sense," Warner told The Register. It's about not losing their base basically as they face these competitors that are dangling shiny objects in front of those customers who have relied on Teradata for many years."īut this raises the question of whether Teradata can grab new customers as more see cloud-based analytics underpinning business activity, especially in web-based commerce. It wants to help them figure out what that architecture looks like as it moves to the cloud. "It has to convince people to build on the investments they've made and see them as investments as opposed to legacy tech. Rusty Warner, Forrester principal analyst, said Teradata's main mission was to focus on existing customers. "We took the harder road in the sense that we maintain compatibility on the APIs so our customers do not have to go through a huge rewriting of everything in order to move to the cloud," he says. He explains that Teradata faced a different set of challenges to the vendors building data warehousing systems in the cloud from scratch as it wanted to keep its existing customers – which include some of the world's largest banks, retailer, and consumer goods firms – by supporting APIs from on-prem systems in the cloud, easing migration. So that basically retired as we moved everything to cloud and object storage," Brobst says. "Rainstor was largely a Hadoop-based infrastructure for on-prem and so on. An example of the volte-face was the 2014 acquisition of Rainstor – maker of a de-duplication engine adapted for Hadoop – which was later retired as Teradata refocused its efforts on cloud and blob storage. But architecturally, I don't actually care if it's HDFS or object store, although I do of course care about implementation cost and total cost of ownership."īut technology developments have caused Teradata to rethink its investments. Nobody in their right mind today would actually be deploying in Hadoop Distributed File System. "When the technology changes and improves, you're still in a good position. "Good architecture is not about technology," Brobst says. SAP patent not inventive enough to get legal protection, judge rulesĭespite being powered by recent developments in cloud computing, Teradata has learned from the Hadoops and "cloud-native" hype cycles that focus on architecture, rather than specific technologies, is the secret to success.Teradata: Public cloud sales soar from low base, majority of business still on-prem.Teradata to take $60m hit for withdrawal from Russia.Teradata takes on cloud-native rivals with data lakes, MLOps.In May 2020, disappointing financials prompted a switch of CEO. "We can afford to keep that raw data in the data lake and retain it and then the data scientists and the power users, they can use that raw data and explore it and decide which data surgically should be promoted in the data product and which one shouldn't, so it's not all or nothing anymore."Īfter the advent of so-called cloud-native data warehouses, which saw Snowflake's spectacular $33 billion IPO, Teradata was perceived as something of a laggard. "Vendors are all trying to claw it into their direction, but when done right the data lake is a good concept to land the raw data and have a low cost retention of that data in its original form," Brobst says. He says the data lake is a "robust" concept, but distinct from the data warehouse, although they should be interoperable and within the same logical architecture.
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