Elevating the Notebook Experience with Databricks' Latest Upgrade
Introduction
Love them or hate them, there's no denying that Databricks does them right, especially after their latest upgrade. Here's a speed run through the new features and my review notes below.
Pros:
Versatile Language Support: Databricks notebooks allow you to use any language supported by your compute environment, making it incredibly versatile for various tasks.
Clean Interface: The interface is much cleaner and more intuitive than before. Almost everything is where you expect it to be, enhancing the overall user experience.
Integration with Databricks AI Assistant: The Databricks AI Assistant pairs exceptionally well with the notebooks. As seen in the video, re-doing prompts was about refining results with minimal effort, not correcting mistakes.
Data Filtering: The ability to filter results without querying is a huge advantage for quick analysis or data exploration.
Superior Design and Performance: Compared to Snowflake's offering, Databricks notebooks are significantly better in both design and performance.
Cons:
Export Limitations: While table results can be exported to CSV, there is no option to export directly to Excel, unlike chart and pivot table results.
Field Hover-Over Information: Hovering over a table name displays all field names and data types, taking up a lot of screen space. Including field types on individual field hover-overs would be more efficient.
Query Integration: If filters used on displayed data could be written back as part of the original query with a click, it would be a neat feature.
Conclusion
Overall, the Databricks team has done a fantastic job with this upgrade. The improvements in look and performance make Databricks notebooks a standout product in the market.
Watch a Quick Walkthrough
For a short, helpful video overview of the functionality, check out this link.