Data Management

Trifacta & Databricks Partner for Faster ROI on Data Lakehouses

Trifacta

Self-service solution removes data engineering bottlenecks, provides clean data and automated pipelines for analytics and machine learning

Trifacta, the Data Engineering Cloud company, today announced a partnership with Databricks, the Data and AI company, around a joint solution that natively integrates Trifacta’s interactive, visual data preparation capabilities into the Databricks Lakehouse Platform. This new joint solution accelerates the development and orchestration of data preparation pipelines by removing bottlenecks that slow data prep for analytics and machine learning models, all while tracking data lineage and ensuring sustainable data governance.

The joint solution has proved essential to organizations modernizing their analytics processes with cloud data lakes and warehouses. With the integration of Trifacta and Databricks platforms, a broader set of data workers can take ownership over the data preparation process and easily collaborate with data scientists and data engineers to better align data products and pipelines with business goals. This visual, low-code joint solution reduces the burden on engineering teams and accelerates an organization’s time-to-insight from data analytics.

“Trifacta offers 1-click data preparation for customers to explore and transform diverse data at scale,” said Michael Hoff, SVP of Business Development, Databricks. “This helps drive more data into Lakehouse for advanced cloud analytics and machine learning.”

“At ABN Amro, we’re focused on democratizing data to accelerate automated decision making. This requires an intuitive approach that allows business users and technical users to collaborate in building high-quality data products. The combination of Trifacta and Databricks enables this,” said Marcel Kramer, ABN Amro Head of Data Engineering.

Trifacta’s integration with Databricks includes support for Delta Lake, enabling data workers to accelerate the process of refining data to feed analytic workloads.

Any transformation executed in Trifacta is translated into runtime Spark code that executes via Databricks, while Databricks automatically scales processing execution based on the parameters of the transformation job. The result is faster, more reliable data pipelines that work as hard as analysts do.

“Data operations are more tightly synced than ever before; no longer are today’s organizations seeking to create siloed data marts or disjointed data teams. And the partnership between Trifacta and Databricks is a perfect example of that,” says Ash Vijayakanthan, Vice President of Alliances, Trifacta. “We’ve made it possible for business users to not only involve themselves in data preparation, but also in the creation and management of data pipelines, both of which were once considered highly technical work relegated to IT teams. We’re excited to see our joint customers yield far greater returns with the ability to accelerate the data preparation process on top of cutting-edge processing power.”

Trifacta offers support for all major cloud platforms; Databricks is available on Microsoft Azure and Amazon AWS. Get started with Trifacta for free today by signing up here.

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