Featured Posts
Introducing Sync Tracking: Enhanced Data Observability and Debugging
Sync Tracking is a powerful new feature in the Observability Toolkit that provides row-level visibility into every record synced in the last 14 days
Announcing Observability Lake: Extend Your Sync Data Retention and Gain Deeper Insights
Observability Lake allows you to use your own cloud storage to retain data, providing extensive historical records and complete visibility into all sync data
Announcing GPT Columns: Clean, Categorize and Enrich in Seconds
Write AI-powered columns to your warehouse without code
Understanding the Context Window: Cornerstone of Modern AI
Discover how advancements in context windows are revolutionizing AI, enabling deeper conversations, better data handling, and more sophisticated outputs across various fields.
How to query Iceberg locally using Spark, PyIceberg, or duckdb
Learn how to efficiently query Iceberg data locally using Spark, PyIceberg, or DuckDB, focusing on catalog types, data storage, and read/write capabilities.
Understanding Iceberg Support in the Databricks Ecosystem
Explore how Databricks integrates Iceberg support via Unity Catalog and UniForm, enabling seamless data management within Spark-based environments.