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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

Over the past two months we’ve made big updates to the SQL node in Observable Canvases. Learn about the friction points we’ve addressed, the solutions we’ve implemented, and what’s in the pipeline. 

Recent improvements to the SQL node in Observable Canvases

Representing data flow is critical in  Observable Canvases because it lets users track data as it moves through branching analyses. Learn how our predictable, user-friendly connectors make it easy to follow the data in canvases.

Visualizing data flow in Observable Canvases

Learn useful features in Observable Canvases that streamline data exploration, speed up data wrangling, and improve organization and navigation in complex analyses.

Eight features supporting fluid data exploration in Observable Canvases

In Observable Canvases we’re building a new way to build dashboards that keeps your data workflow in one place, brings interactive charts to your fingertips, and consolidates collaboration to cut down on tedious back-and-forths. Learn how we’re doing dashboarding, differently, in canvases.

Building a better approach to dashboards in Observable Canvases

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.

Data analysis insights