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The Tableau Foundation's Living Annual Report is a take on the traditional, glossy printed annual report. We share the methodology and design tips from ours to foster greater conversations about transparency and reporting for those working in social good.

When you hear data, what two words come to mind? Take just one minute to share your two words. Don’t worry, there isn’t a right or wrong answer—data means many things to many people. So tell us your two-word definition of data.

Tableau dumbbell charts, also known as DNA charts, are an alternative visualization choice for illustrating the change between two data points. Dumbbell charts get their slang name from their appearance, which look similar to weights, and sometimes strands of DNA, when they are in a horizontal orientation.

I’m pleased to share the Tableau Foundation’s brand new Living Annual Report. We’ve ditched the traditional, glossy-printed annual report for a live report so anyone can get near-real-time information on what we’re doing around the globe.

Oldcastle wasn’t consuming its data in the most efficient way. And as North America’s leading manufacturer of building products and materials (“masonry and hardscapes, otherwise known as sexy concrete,” says Ian), the company had a lot of data.

Here are three lessons I’ve learned through my own journey and through conversation with other women in tech.

Whether you’re a beginner or a Jedi, we have entire courses dedicated to helping you do more with your data. These courses have helped thousands of people to learn Tableau faster than they thought was possible.

At most organizations, the SQL database is sacrosanct. Day in and day out, DBAs protect the write operations and storage requirements of the database to ensure that no matter what, every piece of data is accurately recorded for posterity. Analysis? In most cases, analysis can wait. Extracts can be scheduled at slow times of the day like the early morning. Live connections to the database during business hours (when business users actually have questions) are dangerous and unnecessary. Unfortunately, this limits the usefulness of the data that is being so carefully stored and curated.