October 31st, 2023
Hello friends of Hashboard -
It was great meeting so many of you in San Diego at Coalesce earlier this month! We had a lot of fun with our Chief Marketing Officer, Arthur (opens in a new tab) 🐶, and diving into dbt + self-service data with Hashboard.
Speaking of events, Data Council (opens in a new tab) is accepting speaker proposals until November 8th! I’ll be running the Analytics track again and would love to feature some of you. Submit your proposals here (opens in a new tab) under the analytics category and feel free to reach out to chat through your ideas.
You can now embed external websites (opens in a new tab) in your Hashboard dashboards (say that fast five times in a row)! To add external content in a dashboard, drag the embed icon from the toolbar onto your dashboard section of choice. Add a URL of the content, hit enter and you’re good to go!
We built this feature so users can link external documentation, walk through videos and more to provide their teams additional context and insights included on the dashboard.
You can now easily explore and filter other models and data in your project by selecting the → icon in the attribute tray (opens in a new tab), from a tooltip (opens in a new tab) or from the data tray (opens in a new tab). This will allow you to dive into a new exploration with a filter reflecting the current values automatically applied.
We added another database to our list of connectors! If you’re unfamiliar, MotherDuck is a collaborative serverless analytics platform based on DuckDB, an analytics engine optimized for online analytical processing (OLAP) on your personal machine.
If you require analyzing datasets across multiple external sources in a quick and cost-effective way, MotherDuck could be a great solution. Check out an example (opens in a new tab) of how we analyzed 9 million healthcare insurance claims with MotherDuck and Hashboard. Looking for other connectors? Check out our full list of compatible databases (opens in a new tab) here.
Earlier this year we launched an AI Assistant Beta (many thanks to our tester users!) with the idea that it would accelerate users’ data exploration journeys.
We observed that most users tried it out a couple times and never came back. After analyzing the data we found there were four main failure modes (opens in a new tab), including users overestimating the capabilities and confusion around data filtering.
We pivoted this work to adding more natural language capabilities to our recently launched Data Search (opens in a new tab) feature, which has a more precise interface and works across all the datasets in Hashboard projects. We’d love your feedback on this as we’re still iterating on AI features!
- Data engineers building dashboards?! - If you’re feeling out of your league, we’ve got your back. Check out this blueprint (opens in a new tab) for the end-to-end process of building a metrics dashboard that will actually get used.
- Metrics improvements - Our metrics just keep getting better! You can now manage them in code (opens in a new tab), assign and sort
- Quality of life improvements - Our team has been working hard behind the scenes, with recent investments in improved data upload workflows including BigQuery JSON key files, revamped sharing workflows and guided onboarding experiences.
👀 Hoping to see something else on our feature release list? Check out our Product Roadmap and let us know what we’re missing.
You can drop us a note or ping us on Slack with your💡ideas, 🗣 feedback, or 🙋questions. We look forward to👂hearing from you!