AWS re:Invent Day 1: Matillion, Clutch, and Preparing Data for ML and AI

  • Julie Polito
  • December 4, 2019

Greetings from AWS re:Invent!

We wanted to give you up-to-the-minute info on everything happening here with Matillion, but we’ve been a little busy. Monday saw the launch of the newest Matillion product, Matillion Data Loader. But before we could take a deep breath after that launch, we were swept up in the tide of announcements and excitement of AWS re:Invent.

Matillion goes big at re:Invent

Our newest AE, Bumblebee, working the booth.

At a conference with 65,000 attendees and more than 2,500 technical sessions, it’s best to go big. And that’s exactly what Matillion hoped to do this year. With our brand new booth and a flurry of activity, Team Transform is a big presence on the Expo floor this year, along with a few other familiar names, including Amazon Redshift, Snowflake, Looker and Tableau.

This year, our booth includes a welcome area, a theater section for product and partner presentations (including noise-cancelling Silent Disco headphones), and plenty of demo pods where our solution architect team and product engineers can give people a first-hand look at both Matillion ETL and Matillion Data Loader. The booth has been hopping since the doors opened on Monday.

Matillion ETL, supersized

A packed house for Matillion ETL,  ML, and AI

One of Matillion’s first and best moments at AWS re:Invent was a Product Director David Langton’s packed session on Monday, Preparing Data for reporting, ML, and AI on AWS. ML and AI are certainly on everyone’s mind at AWS re:Invent. The plethora of Amazon Sagemaker product announcements in Andy Jassy’s keynote address on Tuesday only underscored that point.

Speaking to a crowd of more than 300 people, David showed that preparing data for AI is as easy as running an existing shared job in Matillion ETL that gets the data on S3, inspects the Redshift format, uses that information to create a schema, and registers the dataset groupo and ingests the data, then pushes the data out to Amazon Personalize. The whole job took a few seconds, and is similar to how you would prepare data for Amazon Sagemaker or other similar products.

Matillion Director of Product David Langton takes the stage

David shared the stage with Edward Hunter, Director of Business Intelligence and Data Engineering at Clutch, who talked about how Clutch used Matillion to not only create ETL components that can be used with customers that have a similarly high volume of small data transactions, but vastly different data, without having to rewrite anything.  Clutch estimates that it has cut onboarding time for customers by 75 percent, from weeks to days, by using Matillion.

Hunter also talked about how Matillion ETL is helping the company use machine learning to measure brand sentiment by connecting data that their customers have collected with existing social data – without exposing personally identifiable information. In the hyper-competitive retail industry, this capability can, as Hunter says, “Be the key to retailers keeping their doors open, or not.”

To see the whole presentation, go hereTo read more about how Clutch uses Matillion, read the whole case study.

Stay tuned for more news from re:Invent as the show continues.