Reporting and BI
Hex - the practical guide.
Hex is a collaborative data workspace that combines SQL, Python, R and no-code building blocks in one notebook-style interface, then lets you publish the result as an interactive app or dashboard. Founded in 2019, it's become the tool of choice for data and analytics teams that want notebook flexibility, BI polish and real-time collaboration without stitching Jupyter, Tableau and Slack together.
What Hex does
The core is a multi-language notebook (cells can be SQL, Python, R, no-code chart, markdown or input element) with live multiplayer editing similar to Google Docs or Figma. Queries cache and chain together; outputs feed downstream cells; the entire workspace can be published as a polished, interactive app with parameter inputs, tabs and conditional sections.
Magic AI assists with SQL authoring, Python code, chart suggestions and data exploration. Native warehouse and database connectors cover Snowflake, BigQuery, Databricks, Redshift, Postgres and most cloud sources. Scheduled runs, alerts, version history, dbt integration and embedded sharing round out the platform for production analytics work.
Who it's for
Modern data and analytics teams - typically at SaaS, fintech, marketplaces and consumer companies - that want a single tool for ad-hoc analysis, reproducible reports and shareable data apps. Particularly strong for teams of 5-50 analysts who currently bounce between Jupyter, BI tools and Slack screenshots.
Pricing, in rough terms
Per month, billed annually, by editor seats and tier (Free, Team, Professional, Enterprise). Free supports small teams with limited compute; paid tiers start around USD 24 per editor per month and scale with seats, compute and advanced governance features. Viewers are typically free or low-cost depending on tier.
When Hex is the right fit
The right call when SQL and Python are both first-class languages on the team, you publish work to non-technical stakeholders regularly, and notebook + BI in two tools is a friction point. Also a strong fit for data science teams that want their work to land as polished apps rather than static PDFs. A weaker fit for purely business-user self-service (Sigma or Looker), early-stage teams without a real data function, or organisations that need full enterprise BI governance from day one.
Watch-outs
Hex rewards a thoughtful project structure - sprawling notebooks become hard to maintain without naming and ownership conventions. Warehouse compute costs apply just like any BI tool; cache aggressively and watch scheduled runs. The free tier is real but limited; serious teams move to paid quickly.