Locational Big Data – the geospatial data created by mobile devices – is ubiquitous. Smartphones, connected cars, fitness trackers, and more create trillions of location records as their users go about their daily lives. There are many benefits of this Big Data, but one, of course, is large sample size. But just knowing something is “large” is not always enough. Many of our clients want to know more detailed info on sample size for individual projects. It helps them understand certainty of results.
In this blog post, I’ll explain how we’ve updated StreetLight InSight® (that's our easy-to-use online platform for transforming Big Data into transportation analytics) so that our clients always know the size of the sample they’re working with.
I’m thrilled to announce our latest monthly update of StreetLight InSight—that’s our online platform for transforming Big Data into transportation Metrics in minutes. With this release, our platform does even more to close the gap between Big Data and actionable analytics.
We’ve achieved this by adding several new Metrics, updating our databases with the latest location data sets from our suppliers, and implementing features that make StreetLight InSight more user-friendly and responsive. In this blog post, we’ll dive into the most important updates.
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After many years of client requests, we’re releasing the first cut of our StreetLight Volume: 2016 AADT Metric on the StreetLight InSight® platform. These beta Metrics provide a very robust estimate of 2016 Annual Average Daily Traffic (AADT) for almost any road in the US. To learn more, keep reading this blog post, or watch our recorded webinar on the new Metrics. Click here to watch the webinar.
We believe this Metric provides estimates that are comparable or better than most of the standard AADT estimation practices for three reasons: