Data, not code, will dictate systems of the future, says Tecton.ai – SiliconANGLE News

As many companies struggle in the midst of the COVID-19 pandemic, Tecton.ai has managed to garner a $20-million investment fromAndreessen Horowitz and Sequoia Capitalin April 2020.

Tecton.ai was founded by members who created Uber Inc.s Michelangelo, an end-to-end workflow that enablesinternal teamsto seamlessly build, deploy and operate machine-learning solutionsatscale. Through the lessons learned at Uber, the founders of Tecton branched out to create a world-class data platform for machine learning accessible to every company.

So why did this appeal so much to investorslike Andreessen Horowitz? Because while data is the future, wrangling data is still one of the most complex tasks that organizations and data scientists can do. And tools that incorporate machine learning must continue to be developed in order to help enterprises understand the overwhelmingly vast world of data.

I actually think this is probably the biggest shift certainly Ive seen in my career, saidMartin Casado(pictured, left), general partner at Andreessen Horowitz. It used to be if you looked at a system you wrote bad code, you made bugs, you had vulnerabilities in your code that would dictate the system. But more and more, thats actually not the case. You create these models, you feed the data models, the data gives you output, and your workflows around those models are really dictating things.

CasadoandMike Del Balso(pictured, right), co-founder and chief executive officer of Tecton, spoke with Stu Miniman,host of theCUBE, SiliconANGLE Medias livestreaming studio,during a digital CUBE Conversation. They discussed Tectons future, machine learning, and the importance of the data industry.(* Disclosure below.)

The importance of data cant be overstated, according to Casado. I honestly think the data industry is going to be 10 times the computer industry, he said. With compute, youre building houses from the ground up, and theres a ton of value there. With data youre extracting insight and value from the universe, right? Its like the natural system.

In 2020, 90% of business professionals and enterprise analytics say data and analytics are key to their organizations digital transformation initiatives, according to a recent study by Acute Market Reports. Both Casado and Del Balso believe that Tecton has a chance to be a very pivotal company in democratizing access to data. The opportunity is enormous because data is still hard to capture, clean up, and interpret in effective ways. In fact, almost three-quarters (73.5%) of recent survey respondents said they spend 25% or more of their time managing, cleaning, and/or labeling data, according to an Appen Ltd.whitepaper.Andthe demand for data scientists increased32% in 2019 compared to the previous year, according to aDice Tech Jobsreport released in February.

What we dont really know is, how do you take data and reign it in so you can use it in the same way that you use software system? Casado stated. Talking about things like data network effects and extracting data is a little bit preliminary, because we still actually dont even understand how much work it takes to mine insights from data. So I think that were now in this era building the tooling that is required to extract the insights of that data. And I think thats a very necessary step, and this is where a Tecton comes in to provide that tooling.

Tecton is a data platform for machine learning that manages all the feature data and transformations to allow an organization to share predictive signals across use cases and understand what they are, according to Del Balso. During their time with Uber, Del Balsoand the other founders of Tectonrecognized that a feature management layer was the component that really allows a company to scale out machine learning across a number of different use cases, and allows individual data scientists to own more than just one model in production.

In a machine-learning application, theres fundamentally two components, right? Theres a model that you have to build thats going to make the decisions given a certain set of inputs, and then theres the features, which end up being those inputs that the model uses to make the decision, Del Balso explained. And common machine-learning infrastructure stats really are split into two layers. Theres a model management layer and a feature management layer, and thats an emerging pattern in some of the more sophisticated machine-learning stacks that are out there.

At the core of Tectons strategyare a few simple components. The first is feature pipelines, which are data pipelines that plug into a business raw data and turn them into features with predictive signals. The second part of that is a feature store, which catalogs these pipelines and draws the output feature data. The third component is feature service and making data accessible to a data scientist when theyre building their models so they can make these decisions, which is sometimes needed in milliseconds for real-time decisioning.

Were at private beta with a number of customers, Del Balso said. We are spending time engaging in deep, hands-on engagements with different teams who are really trying to set up their machine learning on the cloud, figuring out how to get their machine learning in production. And it tends to be teams that are trying to really use machine learning for operational use cases really trying to drive real business decisions and power their product customer experiences.

Watch the complete video interview below, and be sure to check out more of SiliconANGLEs and theCUBEsCUBE Conversations.

Show your support for our mission with our one-click subscription to our YouTube channel (below). The more subscribers we have, the more YouTube will suggest relevant enterprise and emerging technology content to you. Thanks!

Support our mission: >>>>>> SUBSCRIBE NOW >>>>>> to our YouTube channel.

Wed also like to tell you about our mission and how you can help us fulfill it. SiliconANGLE Media Inc.s business model is based on the intrinsic value of the content, not advertising. Unlike many online publications, we dont have a paywall or run banner advertising, because we want to keep our journalism open, without influence or the need to chase traffic.The journalism, reporting and commentary onSiliconANGLE along with live, unscripted video from our Silicon Valley studio and globe-trotting video teams attheCUBE take a lot of hard work, time and money. Keeping the quality high requires the support of sponsors who are aligned with our vision of ad-free journalism content.

If you like the reporting, video interviews and other ad-free content here,please take a moment to check out a sample of the video content supported by our sponsors,tweet your support, and keep coming back toSiliconANGLE.

More here:
Data, not code, will dictate systems of the future, says Tecton.ai - SiliconANGLE News