The Hex team was at dbt Coalesce in San Diego last week, and I had the tremendous good fortune to meet a ton of you in person! Thank you so much for coming by and saying hello 🙇.
Also at Coalesce:
- Hex won dbt’s Innovation Partner of the Year Award for our Semantic Layer integration (blog).
- Me and my colleague Matt spoke about the metadata architecture behind Hex Magic (recording).
- Amanda from our data team gave a fantastic talk about how we do marketing attribution (recording).
- Honestly just a ton of great talks that have nothing to do with Hex! They’re all on Youtube— binge away.
But that was last week, and I think we agree: the past is over. This week, I’ve got some lovely new Hex features for you across the entire platform, from dbt to debugging. Read on for the updates!
📏 dbt Semantic Layer Cell
Hex’s integration with the dbt Semantic Layer makes it easy to bring trusted metrics and dimensions into your Hex projects, with a drag & drop UI that now features metric search and a snazzy improved layout.
We’ve completely overhauled this cell to support the new v1.6 of the Semantic Layer and use the new dbt Discovery API. We’ve also opened this integration up to more data connections: It’s now available for BigQuery, Redshift, Databricks, and Snowflake connections!
With this cell, technical users can have confidence that the foundational data for their analyses are standardized and approved, and less technical users can use the simple UI to explore company data without writing any code.
Check out the docs to see how to set it up.
☃️ (even more) Native Snowpark DataFrames
Hex already had the best environment for Snowpark work, with one-click sessions and the ability to initiate Snowpark workflows from a SQL cell. Now, Snowpark DataFrames in Hex have the same level of support as pandas DataFrames, fully supporting:
- Chart and Table display cells
- Pivot, Filter, and Writeback cells
- Polyglot SQL → Python → SQL workflows. Just like other DataFrames, now you can query a Snowpark df with SQL, operate on it in Python, query that output df in SQL, and so on.
To answer your first question: We’re not just doing a df.toPandas() in the background! When you use a Snowpark DataFrame in a native Hex cell, the full results are still not pulled into memory— Hex pushes down any chart aggregations, transformation logic, or writeback instructions all the way down to Snowflake, and only fetches that operation’s results into memory.
🐛 Debug mode
It can be hard to figure out what’s wrong with a broken Hex app! You can’t be sure if changes have been made to the notebook since it was last published. You restart & run all, but don’t see the problem— wait, what input parameter values were you using? It can be a total slog.
Debug mode fixes that. Now, if you get an error in a published app, you can enter Debug mode. This gives you a side-by-side view of the app version that’s erroring (with all the input parameters and filters that might be causing problems) and the notebook that reflects that specific app state.
I debugged four old broken apps to test this, and it felt so natural! It was so easy I was actually sort of unimpressed, until I turned the feature off and went to try the old way— and genuinely couldn’t figure out the problem with an app.
Other improvements
- We’ve made improvements to workspace search to better support partial matches. “Rev” is now more likely to match “Revenue”, and so on. We’re continuing to work on improving search!
- We now have multi-tenant HIPAA compliant hosting! Previously you had to be a single-tenant customer to get this, which can come with a lot of baggage. We’re proud to now offer it in a more standard multi-tenant environment.
- Last week was “Hack Week” for the Hex team… so expect lots of interesting little things coming down the line. If you can guess which items from the next couple product updates are the results of Hack Week and not regularly scheduled product programming, I’ll mail you some Hex swag.