Thoughts on the Data Ecosystem

The Blog

Just Binge-Listened to 95 SaaStr Podcasts, Here's What I Learned

February 6, 2017 by Ken Kaczmarek

Who needs a #drinkwithharry?

Over the past few weeks, I tasked myself with listening to all ~32 hours of the SaaStr podcast, in preparation for the SaaStr Annual conference. Each show is an incredibly dense, 20-minute nugget on the business of SaaS. IMHO, it is totally and completely worthwhile to meander through twice-weekly.

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Adding Dynamic Content to a Static Web Page

February 6, 2017 by Dave Williams

Cloud-based data pipes are, by nature, pretty flexible and able to handle a bunch of different kinds of data busywork. One of those uses is to spin up dynamic content without spinning up a server. This makes it possible to host a rich, interactive website on static backends like S3, GitHub, or Forge.

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Lessons from the Data Ecosystem: Part 2

January 4, 2017 by Nate Williams

In my previous post, I covered some recurring themes from our conversations with different user communities in the data ecosystem, which highlight common facets of data projects.

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What We've Learned from Exploring the Data Ecosystem: Part 1

December 7, 2016 by Nate Williams

As we’ve progressed through our private beta, one of the most fruitful activities has been talking with folks in different user communities about their data projects. This has had a profound impact on our product vision and roadmap (including a few major pivots).

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We're Reinventing the Query Builder (Well, Kinda)

November 16, 2016 by Nate Williams

Ah, remember the query builder?

In the brief history of the data ecosystem, the query builder already seems like a relic of a bygone era. Compared to predictive analytics, machine learning, and all the innovation going on around Big Data, the query builder is hardly a shiny new thing.

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Talking With Data Journalists: 5 Takeaways from Our Summer Research Project

September 15, 2016 by Nate Williams

Over the summer, we embarked on a research project to learn more about data journalism and how data journalists work with data.

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