Databricks customers will now be able to get started with Alation directly from their Databricks workspace

Alation Inc., the data intelligence company, today announced that Alation is now available through Databricks Partner Connect.

Today’s data landscapes are complex and highly heterogeneous, with a mix of cloud, on-premises, and legacy systems. As a result, it can be difficult to find the correct data set to use and to know whether that data is accurate. As data-driven decision-making becomes central to every team and business function, and as data volumes and data types have increased, access to trusted data has become a strategic concern.

Organizations leverage the Databricks Lakehouse Platform to unify their data, analytics, and AI. With Alation, data science, data analytics, and AI teams can easily find, understand, and trust their data across both Databricks and non-Databricks data stores. This is accomplished by extending the data discovery, governance, and catalog capabilities built into Databricks and Unity Catalog across other enterprise data sources. With Alation and Databricks’ expanded partnership, customers can now scale data access for lakehouse adoption, discover and migrate high-value data, and with integration with Databricks Unity Catalog, govern and catalog metadata across multiple workspaces. This enables customers to answer bigger, more impactful questions with their data than ever before.

“Alation is crucial to making data a trusted asset throughout the organization,” said Raghu Jayachandran, Senior Manager of Enterprise Data at RaceTrac. “We use it to enable evidence-based analytics and more strategic business decisions. And it’s critical to smarter cloud usage; we gain valuable insights about our data, which help us maintain a cloud environment, provide access to everyone, and foster a data-driven culture. This means we have a clear understanding of which data to migrate, and our data teams can easily find and understand high-quality data within the Databricks Lakehouse with detailed contextual metadata. This improved visibility empowers our teams to enhance analytical models and make confident, data-driven decisions.”

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“Enterprises seeking a modern data infrastructure adopt cloud environments in hopes of being data-driven and accelerating digital transformation,” said Diby Malakar, VP of Product Management, Alation. “But knowing what data to migrate and ensuring everyone in the organization can self-service trusted data in the data lake is challenging. Alation’s Data Intelligence Platform provides visibility into an organization’s data by centralizing the knowledge associated with data: descriptions, policies, origin, and other crucial context. This knowledge powers a single search and discovery interface that informs what data is critical to migrate to Databricks and then enables everyone to find trusted data independently.”

“Organizations need full visibility into all of their data to empower everyone across the business to understand the context of the data being used and to build a data culture,” said Chris Hecht, SVP, Corporate Development and Product Partnerships at Databricks. “Our deepened integration with Alation improves trust and provisions a single view of customers’ data. This enables faster migration, provides visibility, fosters collaboration across data teams to ensure frictionless lakehouse adoption, and facilitates self-service analytics. As a result, data engineers and data scientists can reinforce the value of data as a product across their organizations.”

Alation’s Data Intelligence Platform provides a single view of all an organization’s Databricks workspaces and combines that with the rest of their data. This helps identify the most valuable data to migrate to Databricks and empowers all data consumers to better leverage the Databricks Lakehouse Platform.

Alation for Databricks enables organizations to:

• Provide visibility and trust during migration: Eliminate the uncertainty in data migration by providing visibility to the migration process, prioritizing the most used data, and guiding users to new data in Databricks.
• Facilitate collaboration and build a data culture: Add context and searchable conversations to the cloud data lake to deliver faster and more accurate data science insights, and know which assets can be shared with the entire organization to build a data culture.
• Ensure data integrity throughout its lifecycle: Capture the exact flow of your data over time through lineage. Know where Lakehouse data is, where it came from, and where it’s going.

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