Over the last decade, we’ve seen a renaissance in how data is handled and stored. But the analytics industry missed the memo — we’ve got data, but using it is still a slog. Let’s talk through what’s missing, and how Hyperquery can help.

Analytics is fragmented. 💔

Analytics today operates in four painfully separate tools: the SQL IDE, the dashboard, the doc, and the data catalog. Find data in your catalog, query it with the IDE, visualize with dashboards, and write it all up in a doc. But using so many tools poses some serious problems:

• 📃 Painful, fragmented workflows.
  Single workflows are better when they live in one place. You have a SQL IDE, dashboarding tool, doc tool, and data catalog, meaning you have to go to 4 different apps for every single analysis. No matter how superhuman your focus, you’re going to get a little lost.
• 🔎 Lost work, meaning wasted work.
  If an analysis is dropped in Slack and you can never find it again, that analysis will never influence more than a single decision. Your analysts won’t scale, and you’ll end up repeating work. Analyses need to be created and delivered in the same place to minimize friction to share (meaning more work will be documented) and to centralize the point of access (meaning it’s more easily discoverable).
• ⚫️ Opaque work.
  We’ve all pasted screenshots of plots from our dashboarding tools into Google docs. But no matter how vigilant you try to be about also sharing the underlying query and link to the dashboard, you’ve cleaved your insight from the underlying data, making it harder for other folks to reproduce the work, let alone join in the conversation. Work that should be enlightening is inherently a black box, and analysts regretfully become gatekeepers to their own impact.

SaaS tools have tried to address the above by force-fitting existing solutions into the modern analytics stack, but we believe a new paradigm entirely is necessary.

Introducing Hyperquery ❤️

It’s high time analytics work becomes: centralized, discoverable, and collaborative. These are the three pillars that must comprise a modern analytics experience. We’ve taken great pains to ensure they are foundational to what we’re building at Hyperquery.

📕 Analyses are centralized

We’ve taken the modern doc paradigm of tools like Notion or Coda and placed executable query blocks within it. Seamlessly write queries (even visualize them) alongside documentation so you can create and deliver your analytics work in the same place. The app also lives on top of a basic data catalog, so you can easily get and share context on the data you’re using as well.

💡 Analyses are discoverable

When you’re done with your work, we’ve created a sidebar where you can organize it and make it easily discoverable by your team. Once placed in the public workspace, anyone can search for it with our delightful `CMD+K` search.

🧠 Analyses are transparent

By bringing queries and their results into the doc, technical and non-technical folks alike can dive deeper into your work, and with full multiplayer, conversations can happen in context. Rewindability is also built-in — every query block keeps a record of execution histories, so you never have to second guess a result again.

Get started today

Until now, we’ve been working with a handful of select customers to make sure we were building something that truly solved problems being faced in analytics organizations. We’re finally coming out of stealth and launching into private beta. Get started by navigating to Hyperquery.ai, and let us know what you think.