Mobility Analytics Blog

StreetLight Data Blog

The latest news about Big Data and mobility analytics.

Blog Feature

Big Data  |  Transportation

Evaluating Location-Based Services Data for Transportation: Is Our Sample Representative?

Two of the questions we’re often asked here at StreetLight Data are: “What percentage of the population is creating the location records in your sample?" and "Does the location data in your sample fairly represent all income groups, or is it biased?” In this blog post, we’re pulling back the curtain on our internal evaluation process with a deep-dive analysis of our newest data source: Location-Based Services data. We started using this data source chiefly because of its large sample size and representativeness, so in this blog post, I will show you our process for determining these characteristics. (Click here to read more about Location-Based Services data in general.)

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Blog Feature

Big Data

StreetLight InSight® Update: More Types of Big Data Means Better Metrics – And Better Results

I’m excited to share that we updated StreetLight InSight® again this week – and it’s an update that I’ve been eagerly anticipating for quite a long time. Beginning now, our clients can access Metrics derived from our new Location-Based Services data source directly from our StreetLight InSight web app – that’s our one-stop, cloud-based platform for the best Big Data resources and the processing software that makes them useful. So, why am I so excited about this? It means some of our most popular Metrics are even more comprehensive and accurate than before. That’s because our device sample size now represents about 10% of the U.S. population. We’re processing roughly 60 billion location data points into travel pattern analytics every month – and counting!

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Blog Feature

Big Data  |  Traffic  |  Transportation

Quantifying President Trump’s Impact on Traffic

Since Donald Trump's election on November 8th, 2016, we’ve noticed a major uptick in complaints about traffic in his Manhattan neighborhood. That’s no small feat, especially given that New Yorkers are known for complaining about traffic – just ask Jerry Seinfeld. (For the record, we complain about traffic a ton in San Francisco, too.) However, we hesitate to use subjective grumbling to measure the impact of events. Thanks in part to cognitive biases, people have a tendency to exaggerate traffic and other negative events. Since we were curious about exactly how much travel patterns changed in New York after the election, we decided to use Big Data to crunch the numbers ourselves. (Note: Our study originally appeared in USA Today. Click here to read the article.)

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Blog Feature

Big Data  |  Transportation

Does Transportation Data Actually Matter?

At last week’s Transportation Research Board Annual Meeting, I attended an excellent panel discussion about transportation data. Towards the end of the panel, the moderator challenged the group with a somewhat loaded question. I don’t recall the exact phrasing, but it was along these lines: “As transportation professionals, we know that we have a huge amount of work to do to upgrade, maintain, and repair our infrastructure. The backlog of projects that we have not yet begun is overwhelming. Given our clear mandate - and the often politicized process of infrastructure investments - does all this new data actually impact our decisions in the real world?” It’s an important question to ask - but based on audience feedback and in my own opinion, the answer is clearly yes.

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Blog Feature

The Story Behind Our Name

Occasionally, when I introduce myself as an employee of StreetLight Data, people ask: “Oh, so you measure the data from streetlights?” We do not do that - yet! (But stay tuned for more information on our new partnership with Current Powered by GE down the road)

We're beginning to hear this question often enough that we wanted to publish a blog post about our name. And now is the right time to tell our story: Next week, we will be exhibiting at the Transportation Research Board Annual Meeting, and the StreetLight Data booth (#639) is located near a traffic signal manufacturer.

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Blog Feature

Big Data  |  Transportation

3 Challenges With Transportation Data and How to Solve Them

At the heart of every transportation project lies the need for mobility data. But actually getting accurate, comprehensive data in a cost-effective, appropriate, and timely manner is not always easy. Many transportation planners must rely on costly, outdated data or use time-consuming, assumption-based models to estimate behavior. Although surveys and sensors can certainly reveal important insights, planners who rely solely on conventional data collection tools often struggle to answer important travel behavior questions empirically, accurately, and comprehensively. But transportation planners can take control and get better results by taking advantage of new, more cost-effective, and more effecient data collection and analysis tools. In this blog post, we’ll discuss three key transportation data challenges, and how to overcome them by collecting data that is current and precise, and that describes real-world travel patterns.

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