Learn Practical Techniques for Applying Data Quality in the Lakehouse with Databricks
Databricks
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Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and over 60% of the Fortune 500 — rely on Databricks to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified Data Intelligence Platform that includes Agent Bricks, Genie, Lakebase, Lakeflow, Lakehouse, and Unity Catalog.
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Video Description
Data quality has been a critical and common practice employed across industries for many years. At the core, data quality encompasses six dimensions, including consistency, accuracy, validity, completeness, timeliness, and uniqueness. However, a significant challenge remains in streamlining these processes to prevent data management issues and enhance their utility for downstream analytics, data science, and machine learning. The session will delve into the six dimensions of data quality, detailing the specific techniques and features that enhance the Databricks Platform's functionality. Talk By: Lara Rachidi, Solutions Architect, Databricks ; Liping Huang, Senior Solutions Architect, Databricks Here’s more to explore: Data, Analytics, and AI Governance: https://dbricks.co/44gu3YU Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data… Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc
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