Geography · Economics · Visualization

Google Knew We Didn’t Want to Kill Spreadsheets. We Wanted A Billion Rows.

Study after study shows the negative health impacts of soda.  And 7-11 has responded to market demand with a 128oz Mega Gulp.

For as fashionable as it is in the data community to feign exasperation with spreadsheets and the chaos they cause — mangling numbers and text, crimes against dates and times, relative vs absolute cell references, etc. — Google saw into our hearts and has granted our deepest unspoken wish.

The billion-row spreadsheet.

Actually, it’s wiring up Google Sheets to BigQuery tables so the data doesn’t live in your spreadsheet per se (one good measure of disaster prevention!) but you can manipulate and analyze in a Google Sheet using standard tools e.g. pivot tables.  As Ben Collins noted, the real win is doing work using these familiar spreadsheeting methods instead of writing SQL queries.  Which is true, because SQL is a chokepoint.

“But everyone who works with data should learn SQL.”

And more Americans should learn a foreign language.

When asked how an adult may go about learning a foreign language, the linguist John McWhorter memorably replied “It’s hard. Sleep with somebody, frankly.”  And while readers of this blog skew towards passionate lovers of data, willing to harness SQL for all manner of subqueries and cross lateral joins, the audience of those who merely want to shake hands with their data and answer a couple of questions is much larger.

Audience size and uptake–the key metrics we dismiss too easily.  The spreadsheet is the signal achievement of the PC era and a three-decades track record of being the backbone of quantitative work.  As any UI/UX pro knows, having millions of users willingly engage with an interface and its visual vernacular is very, very difficult.  Despite its drawbacks, the spreadsheet is entrenched for good reasons and for the most part Familiarity Breeds Productivity.

Let’s warmly welcome the Billion Row Spreadsheet as another step forward in the democratization of quantitative analysis.


— Brian Timoney 


Panama Canal photo courtesy of  Helen@littlethorpe ‘s Flickr account

15 Years of Google Earth and the Lessons That Went Unlearned

Google Earth turns 15 this Sunday.  Are you celebrating?

oil production impacts due to Hurricanes Katrina & Rita–extruded data bars ain’t new bro


If you’re a mapping professional, your reaction might be a mix of wistfulness and condescension as you haven’t popped open Google Earth in years let alone dealt with a KML file.  The urge of the carto-cognoscenti to dismiss Google Earth has been strong from the outset, and now all these years later we’re still too slow to acknowledge what it’s gotten right.

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The week after launch I was at a Fourth of July picnic outside Philadelphia where I knew few people, so was uncharacteristically in listening mode.  I remember clearly a not-sober guy with only two things on his mind:  a) arguing with his wife about having a third child and b) a new mapping thing he discovered–

“Go to EARTH DOT GOOGLE DOT COM and download that sh*t!”

That is what Silicon Valley refers to as traction.

It was immediately on its way to be the most successful desktop mapping interface ever.  Despite its popularity–or because of it, honestly–those of us who build and sell web mapping applications continue to draw the wrong conclusions as to what it all meant to us professionally.  Three aspects come to mind:

  •  Google Earth led us to vastly overestimate the average user’s willingness to figure out our map interfaces.  The user experience was so novel and absorbing that people invested time into learning the interface:  semi-complex navigation, toggling layers on and off, managing their own content, etc.  Unfortunately, our stuff isn’t so novel and absorbing and we’ve learned the hard way that even those forced to use our interfaces for work seem very uninterested in even the most basic interactions.
  • A killer use case that the industry still hasn’t replicated is “double-click email attachment, immediately see map content.”  The popularity of Google Earth–and its ultimate penetration in the workplace (especially Oil & Gas / natural resources sectors) — meant you could send a KML file as an email attachment and be somewhat certain you knew what ended up on the recipient’s screen.
  • Users creating and sharing data.  The KML data format combining both spatial coordinates as well as styling made many insiders uneasy.  I wonder if the preference for this tidy segregation didn’t also carry a faint whiff  of the-guild-made-uneasy-by-the-democratization-of-tools.  We never tire of reciting the horrors of Excel while never bothering to tally the benefits side of the ledger:  there’s more than a little of that with KML and how it empowered the masses to create, style, and share spatial data much easier than in the past.

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We don’t hear much of Google Earth these days, though even my recent experience in the energy industry is any indication, its usage and ubiquity still remain strong.  Development of the original application seems to have  mostly stopped and the Mapboxes, Cesiums, and the Cartos of the world have taken up the web mapping mantle.  But what hasn’t been replicated has been the absorption and sense of wonder that a mapping application triggered fifteen years ago this week.

Singapore Harbor and the Failure of Geospatial Marketing

If the global economy were collapsing, how would we know?

In mid-February as parts of Asia wrestled with COVID-19, Twitter user @IAMIRONMAN7 had some data to share and he wasn’t shy about connecting the dots:

As I doom-scrolled through the responses, folks who were familiar with Singapore chimed in that this looked like business-as-usual to them, with anecdata reaching High Art in this flex by a Ben Eliott-Yates:

But what troubled me as a geospatial professional is not one of the tweeters in the thread thought to say “there’s probably data that could answer this question.”

And that’s our failure–the failure of the geospatial industry’s marketing message to resonate even faintly with a crowd willing to debate on social media whether Singapore Harbor was crowded or not.  Because our industry’s default setting is to sell rasters and vectors and point clouds and the complicated tools that are supposed to make sense of it all.

Answers?  That’s the customer’s problem.

Bill Emison recounted how too many LiDAR projects concluded with handing the client a hard drive with a few terabytes of LAS files along with the Net-30 invoice.  For most of us the project is over when we zip our Geotiffs or shapefiles, maybe with some metadata, and email the client a download link.

Will Cadell put it more succinctly at last week’s virtual FOSS4G-UK gathering:

Geospatial people excel at building geospatial things for other geospatial people.

While no one ever starved selling pixels to the NGA, the complacent delivery of the same-old/same-old to the legacy set of tried-and-true set of customers (often, a government entity) has limited our market reach as an industry and left the “vision thing” to others.  You can point to new-ish players like Descartes Labs and Orbital Insight who get this and are building businesses around “answers” and not raw data:  I say good on them and that they’re the exceptions that prove the rule.

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So, was Singapore Harbor unusually crowded in mid-February?

As I wondered about that myself, I came across this web map cooked up by Kristof Van Tricht based on Google Earth Engine which houses a bunch of different datasets including the Sentinel SAR stuff that I knew could answer my question.  Let’s go to the animated GIF:

Maybe it’s the hindsight talking, but to this untrained eye the collapse of the global economy doesn’t seem obvious.

The geospatial industry never tires of trumpeting the ubiquity and centrality of Location.  But until we learn how to deliver meaning and not just raw data pushed through a pipe, the potential of the new markets we’ve been telling each other about for years will remain unrealized, likely to be seized by others.

 — Brian Timoney