Databricks Assistant now also includes features like @-mentioning tables, usage logs, job error diagnosis, AI-generated filters, SQL query optimization, and more!
Over the past few months, we’ve been gathering your feedback and focusing on both the quality of Databricks Assistant’s responses and the overall user experience. Today, we're excited to showcase a more advanced Databricks Assistant, packed with powerful new features all designed to simplify prompt engineering and accelerate your workflows.
Key enhancements include:
Users can now directly @-mention tables in Assistant prompts to improve direct responses. Upon hitting @, users will be provided with a list of tables sorted in order of relevancy. Users can also @-mention multiple tables in prompts. On the right-hand side, users can see full directory/catalog paths.
Previously, the inline Assistant could only operate on entire cells or queries, often regenerating the entire block of code, even when only minor adjustments were needed. Now, we’ve introduced the ability to highlight specific lines within cells or queries, enabling you to target exactly where the Assistant should make changes. This enhancement gives you more control and speeds up response generation.
Admins and managers can now track Assistant adoption and engagement with the newly introduced Assistant system table (system.access.assistant_events). Each row in this table logs user interactions with the side panel or inline chat.
We’ve also created a custom sample dashboard allowing you to quickly visualize information like:
Users can now use the Assistant directly within broken jobs to better understand and correct errors.
Use the Assistant to quickly filter result outputs using natural language. Filters do not require statement re-execution and can be chained together to drill into specific insights.
Leverage syntax highlight warnings and the /optimize command to improve inefficient SQL queries. Optimizations pop up in real-time, helping you quickly identify inefficiencies before execution.
Quick Fix is a powerful new feature that automatically resolves common cell errors in SQL or Python we have high confidence can be addressed by an LLM. This includes errors like trailing commas, typos, syntax mistakes, and more. Designed for speed, Quick Fix delivers suggestions in just 1-3 seconds and is seamlessly integrated with keyboard shortcuts.
To see Databricks Assistant in action check out our demo video to see how you can use Assistant to build data pipelines, SQL queries, and data visualizations. Learn other ways to use the Databricks Assistant to increase your developer productivity by checking out our blog on Tips and Tricks on using the Databricks Assistant