Trusted Data Sets to Revolutionize AI Across Global Enterprises Following Groundbreaking Reltio and Databricks Partnership

September 13, 2024

REDWOOD SHORES, Calif.--(BUSINESS WIRE)--Sep 12, 2024-- Reltio, a leading cloud-native Master Data Management (MDM) platform, and Databricks, a renowned Unified Analytics Engine for Data Engineering, Data Science, and Business Intelligence teams, have announced a landmark partnership. This collaboration marks the beginning of a new era in enterprise AI adoption, enabling businesses to seamlessly integrate and leverage high-quality, trusted data across different departments.

The groundbreaking partnership uniquely combines the strengths of both organizations. Reltio brings its mastery of cloud-native MDM and the ability to maintain up-to-date, reliable data that empower organizations to achieve their digital transformation goals. Meanwhile, Databricks leverages its award-winning Lakehouse Platform to provide fast, and secure data engineering, analytics, and data science solutions.

This merging of technological prowess from Reltio and Databricks enables holistic data insights. These seamlessly integrated data insights facilitate organizations in boosting both data quality and accessibility, fostering an ideal business environment for unlocking AI-driven growth.

According to industry experts, trustworthy data forms the lifeblood of any successful AI implementation. Reliable data is fundamental for producing accurate and helpful business insights that drive informed decision-making at various organizational levels. Since the integration with Databricks is completely cloud-based and highly scalable, it offers a quicker time-to-value and thus meets the ever-rising demand for data-driven decision-making across the board.

The resulting close collaboration between tech leaders, such as Reltio and Databricks, equips forward-thinking businesses with the tools needed to attain their primary objectives in present-day exponentially changing marketplaces.

This powerful synergy brings in a better, more profound enterprise-level approach toward efficient management and usage of high-quality data, not only for maximizing competitive advantage but also expanding efficiency within different business enterprises.

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