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Author: Ted Cuzzillo

A fun, lively path to smarter cities

San Francisco-area designer Steve Pepple wondered whether data could help him explore neighborhoods — on the way to helping city planners build better, perhaps “smarter” cities.

He describes in a fun post on Medium, a genuine “data story,” how he set out to help people find “pockets of activity, vibrance, and new things.”

First, he joined a do-it-yourself project called Sense Your City. Sensors around the world reaped “hyper-local data about environmental conditions, such as noise, dust, light, and pollutants.” That data led to “pockets of activity, vibrance, and new things.” In San Francisco, he writes, “you could see when the fog rolls in.”

That sounds like fun, but could he find a key insights about mobility, housing, or neighborhood change? He had frustrating moments. “I had a bunch of data to work with,” he writes. His many sources included DataSF, San Francisco Planning, SPUR, and the City of Oakland. But he didn’t know what he was doing. Perhaps worse, “I was stymied by trying to find a significant, cumulative insight by cobbling together and analyzing all the data.”

He had been inspired by one man’s discovery who famously found such an insight in San Francisco rental data. Eric Fischer had pored over newspaper ads back to 1948 and surprised urbanists with his conclusion: the usual levers for regulating demand wouldn’t solve the city’s housing crisis.

Smaller experiments

With no big discoveries in sight, Pepple turned to shorter experiments. Apparently as part of a fellowship with Stamen Design and Gray Area Foundation for the Arts, he looked at Instagram photos to track street movement, such as some taken during the 2015 Pride Parade. Data from those photos showed events like parade formation and, in the afternoon, a drift into block parties.

His Medium post includes a short series of visualizations that are more fun and vibrant than you might think any “smart city” has a right to be. With “color quantization,” he created a “spatial database of color” that showed parks and murals in the Mission District. In another map, colors expressed “density of people and establishments,” with brighter and more colorful buildings showing the most active.

Tangible, street-level meaning came in large, street-level screens…that showed passersby how they could “interact with data about their neighborhood and arrive at their own discoveries.”

Clues

It was his work with the urban designers and architects Perkins + Will that his approach had what I find the most interesting and possibly the most meaningful clue. Pepple and team could see and hear neighborhoods with the most activity. Could that be found with data? Indeed, data tracked activity and what people said about the places where it occurred; social media helped characterize those places; mapping tools connected hotspots.

A look at the maps Pepple and team produced shows that transit, living space, restaurants, and other amenities fail to anchor social hotspots. Fine, but why? If the data can reveal this, perhaps it can go the rest of the way.

Keep your eye on Pepple. His playful and often fun analysis puts a bright, even inspiring face on urban data.

Thanks to Stephanie Langenfeld McReynolds, vice president of marketing at Alation, for alerting me to Pepple’s work.

“Radical” change under new Tableau CEO

The changes at Tableau Software in the eight months since CEO Adam Selipsky succeeded co-founder Christian Chabot have been “pretty radical,” says Dan Murray, director of strategic innovation at InterWorks, one of Tableau’s earliest partners if not the first.

“There’s been pretty much of a brain-ectomy” over the last few months, he told me by phone on Friday. People have been leaving.

Whether that’s good or bad might depend on your point of view. To Dan, there’s only good news in the department he cares about most: The development team seems to be intact and performing as well as ever.

He mentioned two technologies in particular whose potential is much greater than most people realize: One that’s already part of Tableau is the data interpreter, the Excel ingest tool. He asks people if they use it, and they shrug. It’s not sexy. “This is going to do a lot more in the next couple of years,” he said.

The other widely underestimated technology is Hyper, the Munich-developed database technology acquired by Tableau in 2016. He compares the potential to the first great re-engineering of the Tableau extract engine five versions back.

The new CEO, Adam Selipsky, “isn’t nearly the stage presence [of Chabot], but he’s a detail freak,” he said. The consensus among employees he’s talked to is that this should have happened a few years ago. “He’s very, very deeply engaged in the business at every level.”

With Seplisky, he said, “you don’t get the husky-eyeball treatment and wow factor [as with Chabot]. But all the employees who’ve been there a while the the tech, operational types are really impressed with the guy. He’s much more in command of the business aspects, more detail oriented.”

He sees new, more seasoned managers coming in. In sales, he said, Tableau now seems friendlier to partners. “The business getting to size where they need a vertical focus,” he said. “It’s the natural evolution.”

What are Tableau’s prospects now as it hurdles toward maturity? “I think they’ve got a lot of juice left in them.”

Take the BARC survey, get a summary of results

The international analyst firm known as BARC, for Business Application Research Center, has been compared to Gartner and Forrester for its broad, vendor-independent assessment of vendors. BARC calls its annual survey “the world’s largest annual survey of business intelligence users.”

The survey has just begun and runs until mid-May. BARC estimates that it takes about 20 minutes to complete. Participants answer questions about their use of BI products from any vendor. BARC compiles the data to analyze buying decisions, implementation cycles, and the benefits of BI products.

All participants will receive a summary of the results and the chance to win an Amazon gift card.

Reach the survey here.

For more information, contact Adrian Wyszogrodzki, awyszogrodzki@barc.de.

“Tame” the data makers

I’ve heard of “taming data.” But the week before last at Strata I heard it in a new context: taming behavior.

Taming data has been “nichy,” as fellow TDWI writer Steve Swoyer puts it. He says, “It doubtless explains the etymology of, for example, Tamr.”

But Swoyer pushes on from there, as Swoyer knows how to do.

[Notice the] consonance between to wrangle and to tame. Both are grounded in the same metaphorical frame. Both are grounded in the same metaphor. This pre-conscious framing/understanding of the issue is more interesting than the stupid terms.

Former IBM sales engineer Lamont Lockwood, now the “Integration Expert,” sees two definitions. One is simple: to straighten and calm streaming data. “You don’t have time to fix it later,” he explains. “You need smart models to keep up.”

That leads to Lamont’s second, “nefarious” definition: taming the users who produce the data. “You’ll be trackable every day and every minute,” he muses, “like call-center workers….This is happening.”

Schmarzo: An over-infatuation with data

The “Dean of Big Data,” Bill Schmarzo, said what I think few of his peers would say on the record: “We have an over-infatuation with data.”

Yet there it was, in the Marriott lobby adjoining last week’s Strata+Hadoop conference in San Jose, CA.

Before you can decide on your data, he insists, you have to decide on your decisions. He said, “That is clearly the biggest challenge in the ‘smart’ conversation,” such as in establishing a “smart city.”

Schmarzo, who is by day Dell EMC CTO, jumped into the “smart city” conversation recently when he joined the San Jose, CA Innovation Advisory Board. His first question was to the airport CTO: what decisions do you face? From there, they could choose data. Must they spot beacons over the terminals, for example, or to use the cheaper and readily available MAC addresses? Such choices could make a difference to that CTO and any tax-starved cities on their way to “smart.”

I asked how people react when he suggests easing up on collecting data willy nilly, consuming it like junk food binges? He paused. “So far, the vast majority are relieved,” he said. “They don’t know what to do with all the data.”

“We over-complicate things, and data vendors are the most guilty,” he said. “They talk about smart this and smart that. And they say ‘You gotta have this technology and these gateways.’ But what will you do with that?”

There’s still one more thing to do: explain the decisions. How can you make the data be made interesting not only for the mayor but the citizens, too? “What I don’t know how to do,” he said, “is how to tell a story around it.”