Governance is critical to democratize data and AI, in the era of LLMs and generative AI. In a typical enterprise, data is siloed across data warehouses and data lakes, making it difficult to manage permissions, understand the usage of data, conduct audits, or discover and share data.
But data isn’t limited to files or tables. You also have modern data assets like dashboards, machine learning models and notebooks, each with its own permission models, making it difficult to manage access permissions for all these assets consistently. The problem gets bigger when your data assets exist across multiple clouds with different access management solutions.
Join Databricks on September 28th from 9AM to 10:30AM PT for their Unity Catalog workshop. With Unity Catalog, organizations can seamlessly govern their structured and unstructured data, machine learning models, notebooks, dashboards and files on any cloud or platform.
In this session, you will learn how to:
Get started with Unity Catalog
Build an enterprise catalog for structured/unstructured data, files, tables, ML models, features across clouds and data platforms
Set up access permissions and audit data access
Leverage AI to monitor quality of data and ML pipelines
Gain comprehensive observability into your data and AI workloads with operational intelligence utilizing built-in system tables for billing, auditing, lineage
Upgrade your Hive metastore to Unity Catalog
Share data across clouds, regions or data platforms
Databricks is the data and AI company. More than 7,000 organizations worldwide — including CMS, CDC, CalHEERS, LA County and over 40% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems.
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