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DIY Data with Trifacta
Efficient Data Engineering for Data Practitioners by Data Practitioners

January 8, 2022

At Trifacta, our mission is to improve the productivity of anyone who works with data. We focus on solving the biggest problems related to data making it better and usable for applications in data science and machine learning. Keeping this in mind, one of our key values is to “start with the user”, which means we want to empower people working with data with an interactive, self-service, and intuitive experience. 

When we talk to our customers, the most common request is about demonstrating practical capabilities of data engineering using Trifacta including connectivity, transformation, profiling, and building data pipelines. As part of our various initiatives to address this important customer need, it has been a pleasure to bring “DIY Data” – a unique webcast series that presents practical aspects of data engineering through hands-on demonstrations.  The series is all about being hands-on with Trifacta through 30-min byte size episodes that are live and interactive. The response to the series has been terrific and we couldn’t be more pleased.

We launched the series premiere of DIY Data in October 2021 showing how Trifacta enables the modern data stack through data on-boarding, integrating with cloud data warehouses and lakes, and achieving the desired data analytics. The outcome was unprecedented with hundreds of customers tuning in, asking questions, and playing it on demand.

We continued with three more episodes as part of the opening season that focused on achieving efficiencies in sales and marketing analytics with Trifacta, flexible approaches to data architectures including ETL, ELT, and custom coding with Trifacta, and achieving SQL-based transformations with SQL-based ELT on Snowflake, the data cloud as the season finale. 

We launched advanced pushdown capabilities for Snowflake at AWS re:Invent 2021. There couldn’t have been a better topic to demonstrate for the final episode of DIY Data season 1. We showcased how Trifacta recipes can be translated into SQL queries that can be run directly on Snowflake making it easier to build the entire data transformation logic and allowing users of all skill levels with data sets of any size. You can sign up for the preview to experience this innovation on the Trifacta-Snowflake page.

If you have not had a chance to be part of DIY Data, it’s not too late. You can catch up on all the episodes of the opening season on the DIY Data page or the Trifacta YouTube channel on demand. But, that’s not all. 

We’re excited to announce the launch of season 2 of DIY Data coming very soon on a screen near you. Season 2 is going to be bigger and better with advanced data engineering capabilities, guest speakers from partners and customers who will demonstrate their use of Trifacta, and more. The season premiere will showcase how you can design a new data analytics warehouse on Google Cloud using Google Cloud Design Patterns. If you want to learn all about data warehouses, Dataprep by Trifacta on Google Cloud, Google BigQuery, and BigQuery ML, you don’t want to miss this episode. David Dinter from Google Cloud will be presenting a thorough practical demonstration on designing an analytics data warehouse for optimized pricing. At the end of the episode, you’ll have access to all the practical resources including GitHub and CodeLab on demand. Register now for this special episode.

Season 2 will continue through the winter and spring of 2022 with special episodes, guests, and everything about data engineering. Please bookmark the DIY Data page for all updates and recordings. If you want to be ahead of the pack, we encourage you to sign up for the free 30-day trial of Trifacta and be ready with your questions and ride along with every episode. See you on your screens soon!