The (Data) Science Behind Google Maps
By Aditi Bhat
Almost all of us use Google Maps, but have you ever wondered how Google Maps work? Google’s biggest asset is data, and lots of it! It collects data every day from a multitude of reliable sources, including your phone. If you have your location services on, Google will be fed with a stream of anonymous bits that speak of location, relative velocity and itinerary.
With the help of data analytics and the data collected from drivers, passengers, and pedestrians, Google’s machine learning algorithms are able to predict traffic jams, help you find your optimal route and even determine which areas should be avoided due to road works or accidents. Enormous amounts of historical data give Google the power to predict traffic patterns.
Putting data to use
SAP and Google are working together and pairing enterprise applications with the kind of consumer tools that enrich millions of people’s lives every day. This is done while navigating the complexity of data science and big data analytics, or the growing volume, variety and increased velocity of information. Following are some examples of a multitude of uses from intuitive mapping tools:
- A telecom operator could use Google Earth to perform dropped-call analysis and pinpoint the geo-coordinates of faulty towers.
- A state department of revenue could overlay household tax information on a map of the state and group it at the county level to track the highest and lowest tax bases.
- A mortgage bank could perform a risk assessment of its mortgage portfolio by overlaying foreclosure and default data with the location shown on Google Maps.
- A team of customer support representatives in a consumer packaged goods company could collaborate and pinpoint the location of consumer complaints within specific geographies and determine how to address the issue.
The US census data could be overlaid on a Google Map of the country, grouped by state and drilled down at a county level.
What’s in store?
Google Maps is becoming increasingly significant for businesses, government agencies and the average Joe. A lot is going on behind the surface to make it precise, accurate and useful.
Google has acquired the likes of Skybox and Waze to improve its predictions and data sources. Waze, a leading community-based navigation and traffic app, relies on its users to report accidents, bottlenecks, and traffic as they drive. It also partners with local city authorities to elicit accident data, construction updates, road closures, etc. This data allows Google, to make adjustments in real-time.
Skybox, a high-resolution imagery company improves the accuracy of Google Maps. A team of data scientists then write algorithms that extract relevant data like street numbers, heights of buildings, speed limits, traffic signs and turn restrictions. It even makes corrections to the maps based on user data.
The science behind Google Maps is beyond complex and yet data scientists using data analytics and scores of information, make our lives so much easier. It won’t be wrong to say, Google Maps is trying its best to ensure that you never get lost on the streets again!