Streamlined transformation tool improves recovery from failure, optimizes performance and enables end-to-end resilient data infrastructure.
SAN FRANCISCO – June 3, 2019 – Fivetran, which builds automated technology to help analysts replicate data into cloud warehouses, today unveiled its new in-warehouse transformation product, Fivetran Transformations, at the Snowflake Summit data conference. Designed to bring simplified, fail-safe data transformations to Fivetran’s automated data pipeline solution, the agile end-to-end tool enables data teams to execute SQL when new data arrives or on a schedule. Users of Snowflake’s warehouse platform can now trial the feature for free; support for additional database and warehouse destinations, including Google BigQuery, Amazon Redshift and Microsoft Azure, will roll out soon.
Fivetran Transformations is an extension of the software company's 100+ pre-engineered data connectors. The new tool features everything needed to orchestrate SQL-based transformations in the data warehouse, as opposed to antiquated data pipeline technology, which applies transformations before the data enters the warehouse. By putting an automated transformation tool inside the warehouse, as Fivetran does, the original data is protected and available should a restore be required. This delivers enormous scalability and the ability to recover from failure, as well as significant time-saving benefits.
“Fivetran is all about keeping it simple — that’s why our data pipelines are zero-configuration,” says George Fraser, co-founder and CEO at Fivetran. “The new Fivetran transformation tool is the ideal companion to our data pipelines. It allows our users to solve complex problems without wrangling infrastructure so you can focus your efforts on creating insights for your business.”
Fivetran is built on the idea that configuration-heavy ETL (extract, transform, load) protocols are outdated and burdensome in today’s cloud-based data environments. Its zero-configuration ELT (extract, load, transform) model reduces risk, conserves analytical and technical resources for strategic projects, and allows for greater business agility to deploy new tools and scale across an organization.
"Fivetran’s new transformation tool is the embodiment of modern ELT design and offers clear advantages over traditional ETL, which isn’t built to harness cloud capabilities,” Snowflake Partner Ecosystems Product Manager Harsha Kapre said. “Since the transformation tool is integrated with the data warehouse, users can make the most of an extremely performant and infinitely scalable cloud-built data warehouse architecture, like Snowflake.”
Fivetran Transformations integrates seamlessly with the company’s automated data platform solution and features simplified management of the entire pipeline in a single tool. The robust logging and notification system makes reporting easy and enables teams to quickly diagnose and resolve errors.
“The new Fivetran Transformations tool makes a ton of sense," says Mike Fuller, Senior Solutions Architect at Red Pill Analytics. "You don’t need to go to a lot of effort to get your transforms to work, and users can view, add and manage transformations within the Fivetran dashboard. Fivetran has done all of the hard work by figuring out various APIs and database connectivity, so this transformation product continues their tradition of simplifying analytics.”
For more information about Fivetran and to trial its new transformation tool for free, visit fivetran.com.
For companies looking for a strategic partner to help them with the transformation tool, or to build out a modern data strategy using Fivetran, partners from the company's global network of system integrators are ready to provide assistance, including Interworks, Das42, Redpill Analytics, Analytics Academy, Sutter Mills and Decisive Data.
Shaped by the real-world needs of data analysts, Fivetran technology is the smartest, fastest way to replicate your applications, databases, events and files into a high-performance cloud warehouse. Fivetran connectors deploy in minutes, require zero maintenance, and automatically adjust to source changes — so your data team can stop worrying about engineering and focus on driving insights.