Blog post thumbnail - 8 things data teams should know about Framework

Canvases first look webinar

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Hanna Woodburn headshot

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Allison Horst headshot

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Hanna Woodburn

Allison Horst

Robert Kosara

One way we keep Observable Canvases fast (even when displaying dense, branched, visual analyses) is by virtualizing rows and columns that aren’t currently visible to users. Read on to learn the basics of table virtualization, and how it improves canvas performance.

Table virtualization in Observable Canvases

Joins are a cornerstone of data wrangling, but are surprisingly challenging to build as UI-based operations. Get a behind the scenes look into why joins are hard, and how we handle them in Observable Canvases. 

Challenges underlying the humble data join

Our biggest release yet for Observable Canvases is here with new chart types, support for internal embedding, and dashboard creation.  


Observable Canvases: New chart types, dashboards, and easier ways to share

Data teams are rapidly adopting AI tools to boost data analysis workflows from initial exploration to dashboard development. Learn three ways that AI can improve exploratory data analysis with examples of each in an Observable Canvas.

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.

How to query databases for data analysis

An introduction to database basics for analysts, covering the basics of how they work and why they are structured the way they are.

Databases 101 for data analysts

Exploring a new dataset? Follow these key steps to make sure you know what the data is, that it contains valid and meaningful data, and that you know what might be missing.

How to explore data: A checklist for navigating datasets

Discover how to use Observable Framework alongside a suite of essential tools like Node.js, npm, static site generators, and data loaders to power fast, interactive data apps.

Data analysis insights