Trifacta Launches Industry First Data Engineering Cloud

Source: Trifacta

Trifacta recently announced the release of Trifacta Data Engineering Cloud, a major expansion of its visual data preparation platform. The product is headlined by multi-cloud support with solutions that are optimized for each platform. Users can choose between ETL or ELT, or an optimal combination of the two based on cost. Trifacta Data Engineering Cloud also touts universal connectivity to more than 180 enterprise data sources both on-prem and in the cloud. Trifacta’s cloud integrates with all toolchains as well.

Trifacta offers a suite of what its dubbed ‘data wrangling’ tools in three different iterations: Trifacta Starter, Professional, and WEnterprise. Trifacta allows users to do data prep without having to manually write code or use mapping-based systems. The Predictive Transformation function enables the exploration of data content so users can define a recipe for how the data should be transformed. Data Wrangler also includes data discovery, structuring, cleaning, enriching, and validation capabilities.

The Trifacta Data Engineering Cloud includes a visual “guide and decide” interface that utilizes machine learning to make understanding and resolving data transformation challenges intuitive to any user persona. Active data profiling extends beyond traditional data quality rules as well. Users can also model data flows while managing relationships across data sets and recipes. Self-service capabilities are headlined by low-code and no-code authoring, macros, templates and knowledge sharing, and usage-based pricing.

In a media statement about the news, Trifacta CEO Adam Wilson said “Accelerating data preparation and democratizing ETL for these users and their cloud data warehousing projects requires an enterprise-grade data engineering platform that is open, intelligent, and self-service. We’ve created the Trifacta Data Engineering Cloud to meet these needs.”

Watch The Trifacta Data Engineering Cloud on YouTube or read Connect your Data from Anywhere for Data Engineering in the company’s blog to learn more.