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The medium is the problem 

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Canvases first look webinar

State of BI and analytics

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The role of inquiry in AI-powered data analysis

Hanna Woodburn

Allison Horst

Julio Avalos

Observable

Robert Kosara

In this guide, we share a practical framework for streamlining your data analysis process, helping you transform vague requests into clearer data visualizations and valuable insights.

From raw data to data storytelling: A framework for structuring any analysis

AI makes it faster and easier than ever to get answers from data — but the quality of the questions being asked matters more than ever. We share a practical framework for building better inquiry habits across your team.

The role of inquiry in AI-powered data analysis 

AI code generation produces more code faster, but widens the comprehension gap — the solution isn't better generation, it's restoring the "write, run, inspect" loop at machine speed.

The medium is the problem

AI is reshaping workflows across the data analysis and BI landscape. We took a look at where AI is delivering real value for data teams today, where it misses the mark, and how to unlock its full potential — without losing the human ingenuity that drives meaningful insights.

How AI is accelerating data analysis work — and where it’s falling short

Don’t stumble into common data analysis pitfalls. Learn how to avoid issues related to missing values, data wrangling mistakes, and AI-generated outputs.

4 ways to avoid common gotchas in data analysis

The analytics and BI industry is changing rapidly. In this post, we recap the major shifts in the BI landscape, forecast where it’s going, and outline how you can keep up. 

The state of BI and analytics in 2026

Data teams are rapidly adopting AI tools to boost data analysis workflows from initial exploration to dashboard development. Learn three ways to use AI in exploratory data analysis for fast data profiling, data wrangling, and chart prototyping.

Three ways to use AI for exploratory data analysis

Visual data analysis helps data teams keep a close eye on their data throughout the entire analysis process. Learn how that expands opportunities for discovery, facilitates collaboration, and helps uncover mistakes sooner than later.

End-to-end visual data analysis improves discovery, accuracy, and collaboration

When collaborators are only involved as an afterthought in the data lifecycle, analysts can find themselves mired in unexpected last-minute requests, or overhauling deliverables that didn’t match stakeholder needs. By involving collaborators from the start, analysts can do more focused, efficient, and valued work with fewer back-and-forths.

Move faster, together, with collaborative analytics

A look at the basics of querying databases using SQL, to count values, add up numbers, and compute averages. We also cover filtering data to only consider specific values.

Data analysis insights

From raw data to data storytelling: A framework for structuring any analysis

The role of inquiry in AI-powered data analysis

The medium is the problem

How AI is accelerating data analysis work — and where it’s falling short

4 ways to avoid common gotchas in data analysis

The state of BI and analytics in 2026

Three ways to use AI for exploratory data analysis

End-to-end visual data analysis improves discovery, accuracy, and collaboration

Move faster, together, with collaborative analytics

How to query databases for data analysis