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AtScale Powers Databricks Genie with Semantic Layer Delivering Accurate and Trusted Natural Language Querying

AtScale Powers Databricks Genie with Semantic Layer Delivering Accurate and Trusted Natural Language Querying

Nicole Francoeur
nicole.francoeur@atscale.com
AtScale

AtScale, a leader in s emantic layer technology, today announced its groundbreaking integration with Databricks Genie, bringing powerful natural language querying to the Databricks Lakehouse. This strategic partnership empowers business users to ask complex questions in plain language and receive accurate, real-time answers, significantly enhancing decision-making without requiring SQL expertise.

Integrating AtScale’s semantic layer with Databricks Genie revolutionizes how users interact with data by delivering consistent and governed insights across all business intelligence tools, including Power BI, Tableau, and Excel. This unified approach ensures that every user—from executives to frontline decision-makers—has access to a single source of truth, eliminating data silos and fostering a data-driven culture within organizations.

Key Benefits of the Integration:

  • Accurate and Consistent Insights: AtScale’s semantic layer ensures consistent answers across all BI tools, improving query accuracy from approximately 20% to over 95% by providing clear, governed definitions for business metrics.
  • Faster Performance and Reduced Latency: The AtScale query engine translates natural language questions into optimized SQL queries for Databricks SQL (DBSQL), significantly reducing latency through intelligent query optimization and pre-aggregation.
  • Democratized Data Access: By masking the complexities of underlying data structures, AtScale simplifies data interaction, enabling business users to self-serve insights without needing technical skills or SQL expertise.
  • Unified Semantic Lakehouse Experience: The integration establishes a governed and scalable Semantic Lakehouse on Databricks, ensuring consistent and secure data consumption across all analytics platforms.

"The integration of AtScale’s semantic layer with Databricks Genie enables a new era of data accessibility, where business users can ask complex questions in plain language and instantly get accurate, consistent answers. This is a significant leap forward in empowering data-driven decision-making," said David P. Mariani, Founder & CTO of AtScale. "With AtScale and Databricks Genie, organizations can harness the full potential of their data to drive impactful business outcomes."

The AtScale and Databricks partnership, which began in early 2022 with a vision to democratize data access and eliminate unnecessary data movement, has evolved into a comprehensive solution that unifies the power of Databricks Lakehouse with AtScale’s semantic layer, forming the Semantic Lakehouse—a tool-agnostic, governed platform supporting advanced analytics and artificial intelligence. This integration transforms manufacturing, retail, finance, and healthcare industries, enabling real-time decision-making and consistent metrics by leveraging open-sourced Semantic Model Repositories for enhanced data consistency and governance.

For additional information, read the announcement Blog or Request a Demo.

About AtScale
AtScale enables smarter data-driven decisions by bridging the gap between data and analytics, simplifying and extending BI and AI capabilities. With its Universal Semantic Layer, AtScale empowers enterprises to create business-friendly data models that ensure consistency and accuracy across analytics tools. With over a decade of innovation, AtScale continues to lead the industry, transforming how enterprises utilize and analyze their data. For more information, please visit www.atscale.com and follow us on LinkedIn.

About Databricks
Databricks is the lakehouse company that provides a unified platform for data engineering, machine learning, and business intelligence. Databricks Genie enhances this platform by enabling natural language querying, making data accessible and actionable for all users.


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