Turning Traffic-Related Big Data into Information: Webinar

Join INRIX for a Webinar on August 16
Reserve your Webinar seat now

Date: Thursday, August 16, 2012
Time: 1:00-2:30pm EDT  (10:00-11:30am PDT)

INRIX Analytics combines the best traffic data and analytic tools – in the cloud accessible from a browser

INRIX Analytics is the result of collaboration with the University of Maryland’s CATT Lab based on software developed for the I-95 Corridor Coalition and its member agencies as part of the Coalition’s Vehicle Probe Project.  Since 2008, the Project has mined crowd-sourced traffic data with advanced analytics techniques to turn billions of data points into powerful insights that can now be extended to help all agencies take a smarter approach to how they build, manage and measure their road networks


Ted Trepanier, INRIX Sr. Director of Business Development, Public Sector




Pete Costello, INRIX Director of Business Development, Public Sector




INRIX Analytics helps metro, regional, state and national transportation agencies drive cost out of daily operations, pinpoint areas that most benefit from road and transit improvements and better measure the impact of their investments.

Quality analytics starts with quality data.  In the largest ongoing test of traffic data quality in the world and under a variety of road and weather conditions, the University of Maryland found INRIX data accurate within 2 miles per hour of actual travel speeds across 30 site tests in seven states over the past three years, 24 hours a day, 7 days a week.

Join over a dozen state DOTs and 20 MPOs that are using INRIX Analytics today!

Find out more about INRIX and INRIX Analytics.


VC’s Pour Record $1 Billion into Big Data Firms in 12 Months

Big Data companies Q2 investments grow 400% Year over Year

https://encrypted-tbn1.google.com/images?q=tbn:ANd9GcRLfmwVOxe4_9h5jCcK3ZFd9LhKc83x-QKman41TZrxjG_Jf9S2If Venture Capitalist’s can see the future (and often they forecast it correctly), Big Data companies are about to pop.

According to research firm CB Insights, VC invested $1 billion into Big Data firms over the past 365 days, including $460 million in the Q2 alone.  Wow. Wow. Wow.

That Q2 dollar total is 400% the $114 million in VC funding for Big Data in the Q2 of 2011, and is 5x the $87 million invested to Big Data companies in the Q1 of this year.

Here are the Venture Capital investments for the past 5 quarters:

Q2 2012 — 25 investments, $460 million, $18 million average

Q1 2012 — 20 investments, $87 million, $4 million average

Q4 2011 — 17 investments, $285 million, $17 million average

Q3 2011 — 18 investments, $201 million,  $11 million average

Q2 2011 — 10 investments, $114 million, $11 million average

Annual data on investments from Thomson Reuters, shows Big Data investments is firmly on the upswing:

2011 — $2.5 billion

2010 — $1.5 billion

2009 — $1.1 billion

Why is the CB Insights’ VC dollar amounts for 2011 ($600 million for the 3 quarters shown) so much lower than Thomson Reuters’ $2.5 billion?  I suspect its because the two firms use different classifications in investments.   Needless to say, with this level of investment surely information and insight will emerge from all this data… Time will tell.

Big Data: Small Screen – Location-Based Services 2.0

Big DataBig DataBig Data.  We’re hearing about it more and more every day.  Mobile.  Mobile. Mobile.  We hear about it seemingly every hour.  But where do these two industry tectonic plates come together?   They collide in the area of Location-Based Service (LBS) 2.0.

But first, let’s take a moment to ensure we have a shared understanding of where we are today with LBS 1.0.   Something I call, “Small Data: Small Screen.”   I’ll do this landscape with an area I’m most familiar with, the “navigation” category of mobile apps evaluating our efforts in terms of Gold, Silver and Bronze medals in the spirit of the Summer Olympics that’s kicking off in London.  These are those apps who promise to help consumers by giving them permission to “use your location” to make it easier to find a restaurant, avoid traffic or get turn-by-turn directions.

Small Data: Small Screen – LBS 1.0 {Overall Score: Silver

As a whole, there are three emerging sub-categories of “Navigation” apps: i) Local Search, ii) Turn-by-turn driving and iii) Traffic apps.  Let’s take a quick tour of each sub-category.

i) Local Search Apps {Bronze}:  These are the Google Maps, Bing, Yelp, Where, Around Me type apps.  These apps answer the LBS 1.0 questions of “What’s around me?”.  More specifically, “Where can I find retailer X?”, what’s the address of Y store?”, “What are the ratings of Z restaurant?”.   As an industry, I give us a Bronze medal.  We solve many useful problems as evidenced by recent Microsoft research finding 70% of mobile searches are acted upon within sixty minutes, as compared to desktop searches which are only acted on 70% of the time within 1 week.

However, we have some colossal fails as an industry.  For example, industry researchers report Home Depot is the 8th most searched brand on mobile.  Seems odd, right?  Doesn’t every homeowner know how to get to their local Home Depot?  However, the question people actually are asking is, “What are my local Home Depot’s hours?”, because they don’t want to drive across town on a Sunday night only to discover the store is closed.  However, the Home Depot mobile app, doesn’t quickly answer this question.  Instead it tries to sell me a major appliance while I’m driving down the freeway.  FAIL.   One of INRIX’s own licensees, TeleNav, found the most searched place in their navigator app is…get ready for it… Starbucks.  Were people really struggling to find a Starbucks?   What they really wanted to know was the closest Starbucks to their location as well as if it was open.   Again, an easy fix but also a big FAIL as an industry.  TeleNav is hardly alone.

ii) Turn-by-turn driving apps {Silver}:  These are the Motion X, Garmin, TomTom, Waze, AT&T Navigator, type apps.  They answer consumers’ next logical question, “Once I’ve found the location and know the store is open, how do I get there?”  While a very popular category for consumer downloads, these apps typically only are used twice per week.  How can this category be so hot yet usage be so low?  The problem is the information provided by these apps is often inaccurate, not updated in real-time and lacks useful, actionable insight for the consumer.   Road closures, major construction, concerts and major sporting events are always of happening.  Most of these apps are ignorant of quality real-time data that makes the difference between routing someone through traffic or around it to their desired destination or doesn’t factor in delays due to traffic into travel times.   FAIL.  It’s 2012, not 2010.  As an industry, we can still do much better.

iii) Traffic apps {Bronze}.  You might be shocked to learn there are over 700 traffic apps in the US Apple App store alone.  These are the INRIX Traffic, Beat The Traffic, SigAlert, Dept of Transportation apps and the like.  Today these apps typically paint “traffic on map” in various states of quality and roadway coverage.  They typically answer the question ‘What does traffic look like a short time ago?”.  {Disclaimer, I am employed by INRIX where we analyze traffic data to provide insight that makes navigation easier and informs design of intelligent transportation networks}.    Why the Bronze medal when these apps do a much better job of providing the traffic than the intermittent radio broadcasts?  Because people don’t want to know there’s traffic – anyone who commutes more than 10 minutes a day knows there’s always traffic at rush hour.  What they really want to know is “Given the traffic, what’s my fastest route home, how long will it take and will I be able to get to my destination in time?”

Big Data: Small Screen – LBS 2.0

So what exactly is Big Data?  Other than another buzz word like “cloud computing” that means little to the average consumer, the phrase loosely means data so complex and generated in such volumes that when mined using sophisticated analytics reveals insights that provide new ways that more effectively tackle big problems.  Splunk, Facebook and INRIX are three good examples of Big Data companies.   Splunk is taking Business Intelligence to the next level mining machine data.  Facebook is swimming with data that investors are banking on the company leveraging to drive revenues that help Facebook live up to its huge valuation.   At INRIX, we capture, analyze, and visualize more than a trillion data points from nearly 100 million drivers and hundreds commercial, consumer and government sources to produce real-time traffic updated every minute across 30+ countries.   In an industry where analytics and minimizing data latency are keys to quality, three minute old traffic data crowd-sourced from a small number of drivers just doesn’t cut it.

So, here’s our industry challenge.  How do we leverage Big Data to deliver apps and services on mobile devices to answer the questions consumers really care about?    How do we turn information into useful insight that consumers can depend on to help simplify their lives?  After all, I want my phone to give me insight mined from all human knowledge available on a topic right now, relevant to me and nothing short of this goal.

If we look back at the navigation apps as our example, these are the questions we must answer in an LBS 2.0 world:

  • “What are the cheapest gas stations on my way, not around me, to the airport rental car location?”
  • “Which coffee shops around me are open right now?”
  • “What’s the fastest route to that coffee shop, given real-time traffic?”
  • “Do I have enough time to grab a latte and still get to my son’s game on time?”  I need more than just an estimate but my actual arrival time, given real-time traffic conditions on the way there.”

By 2014, the acronym ‘ETA’ should join the dust bucket of ‘VHS’, ‘VCR’ and others.   To illustrate, when you want to know the time of day, you don’t look at the position of the sun in the sky to get an estimated time of day, you simply look at your phone and know the actual time.  Arrival times will follow this trend, given the Big Data trends underway right now.

My prediction for 2013’s overall score is a Silver medal as the industry and consumers start to separate the pretenders from the contenders delivering real value, not just hype.  By 2014, I’m hopeful as an industry that we’ll grab the Gold.

Yes, we have a few technical barriers and privacy issues in front of us, but I’m confident we will find our way through all of these, given the amount of R&D being poured into Big Data and the power of the consumer to demand fairness in terms of privacy.   Regardless, the LBS 2.0 starter’s gun just sounded.


Welcome to Big Data

Big Data is data so large and heterogeneous and fast that normal systems and processes of the 90’s and ’00s can not handle them.

We often speak about the Big 3 Vs: Volume, Variety and Velocity.
If you are a technologist or just plain interested in following the industry.  Follow our journey as we together turn Big Data into Big Information and Big Insight.