Databricks has announced the public preview of Lakehouse for Data Warehousing, which aims to enable more efficient data management and analytics by integrating data lakes and data warehouses. This new platform allows users to run SQL queries directly on data stored in a lakehouse, providing enhanced performance and capabilities for data-driven decision-making.

Star and snowflake schemas are two essential dimensional modeling techniques used in data warehousing, each with its own advantages and disadvantages for organizing data for analytics. Star schemas prioritize read performance with denormalized tables, while snowflake schemas introduce normalization to reduce redundancy and improve data integrity, albeit at the cost of query complexity and performance. Understanding these differences is crucial for data and analytics engineers when designing effective data models in modern tools like dbt.