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Trifacta at AWS re:Invent 2021
A Retrospective

December 16, 2021

AWS re:Invent marked a return to in-person events in 2021 and for us, it was a great venue to launch new capabilities on Trifacta, the Data Engineering Cloud, meet customers, partners, and make new friends through the week. 

At the outset, it was exciting to announce our latest innovation in data transformation with SQL-based ELT leveraging our Pushdown Optimization capabilities on Snowflake, the Data Cloud. With this announcement, you can leverage self-service data transformations on Snowflake with a no-code/low-code solution using our visual and intuitive interface. We’d love for you to test drive this solution and looking forward to you signing up for the preview.

It was also a wonderful opportunity to learn, network, and discuss data through the various product announcements, breakout sessions, hands-on workshops, and conversations around various aspects of data, analytics, transformation, and management. Apart from our launch, a few highlights stood out for me.

  1. Multiple product announcements focused on the data space across keynotes (from Adam Selipsky, AWS CEO, and other AWS leaders), leadership sessions, and breakout sessions.
  2. Serverless extends its presence into the analytics and AI/ML space with a slew of product announcements. 
  3. AWS’ strategy and priority on data, analytics, and AI/ML with the Databases, Analytics, and Machine Learning (ML) keynote by Swami Sivasubramanian, VP, Machine Learning.
  4. Storage and Access Control remain strategic priorities for AWS with incremental innovations and improvements on Amazon Simple Storage Service (S3) and AWS Identity and Access Management (IAM).
  5. Enterprises continue to move to the cloud to leverage the scale and performance of the cloud.

From our perspective, we’re excited to see how Trifacta can be complementary to many of these announcements given our focus on data engineering. 

Serverless continues to grow

In the recent past, serverless solutions have grown in popularity across many stacks starting with compute and moving up into application development. It’s time for data engineers to reap the benefits of the innovations with serverless. Let’s dive deep into some of the announcements at re:Invent 2021.

AWS announced Amazon EMR Serverless, a new serverless option in Amazon EMR that makes it easy and cost-effective for data engineers and analysts to run petabyte-scale data analytics in the cloud. With this announcement, you can now run applications using open-source frameworks such as Apache Spark, Apache Hive, and Presto without the need to configure, optimize, or secure clusters. For our customers using Trifacta on AWS, this means there are fewer knobs to size your clusters, less infrastructure to set up and maintain, and reduced costs when not in use. 

Serverless featured on the cloud data warehouse service with Amazon Redshift Serverless. With this new announcement, you can just load your data and start querying without setting up and managing clusters. Redshift Serverless will automatically provision the right compute resources and adapt to any changes. We believe our customers can benefit hugely from these advantages.

AWS’ flagship machine learning service – Amazon SageMaker now provides a serverless inference option with Amazon SageMaker Serverless Inference that enables you to easily deploy machine learning models for inference without the need to configure or manage the underlying infrastructure.

Machine Learning Keynote

The Data+ML keynote by Swami highlighted that data is the fuel for machine learning. For us in Trifacta, it was great to see “Data Preparation” as a key part of the machine learning stack.

During the keynote, it was exciting to see the announcement of Amazon SageMaker Canvas, a visual, no-code machine learning capability for business and data analysts. This aligned with Trifacta’s positioning of a no-code solution delivering consumable data for data analysts. SageMaker Canvas comes with a visual user interface that lets you browse and access data sources, combine datasets, train models, and generate new predictions when new data is available.

Amazon S3 and AWS IAM continue to be innovative

It was heartening to see innovations and improvements to Amazon S3, despite being the first service launched by AWS 15 years ago! A couple of announcements stood out for me that focused on simplified access management for data stored in Amazon S3. A new setting called Amazon S3 Object Ownership lets you disable access control lists (ACLs) to simplify access management. Secondly, the Amazon S3 console policy editor now reports security warnings, errors, and suggestions powered by IAM Access Analyzer as you author complex cross-account S3 policies.

As we see our customers transform more and more data hosted on S3, these enhancements make it easier to configure S3 buckets for better data security and control. We’re looking forward to supporting our customers with these continued enhancements on AWS.

Enterprises migrating to the cloud

While it seems AWS is leading the cloud with an impressive 32% market share, Adam Selipsky, CEO of AWS believes this is just the beginning. Adam shared that only ~15% of IT spending has moved to the cloud and sees it as a tremendous opportunity both for AWS and for enterprises to innovate in the cloud for years to come. His keynote also included AWS customers from different verticals sharing their journey and successes. These stories were not only interesting but also inspiring as we look at our own story and experience with our customers.


In summary, I had a great time at AWS re:Invent with our launch featuring ELT on Snowflake, learning from our customers and partners, and most importantly meeting people in person. I realized how much I have been missing this for the last 18+ months.