We believe that there is collective value in the massive amount of data arising from all of our sensors across the globe. And most importantly, we believe this data can be used to improve safety, infrastructure, and productivity for our customers. To better understand what we mean when we talk about data analytics at Geotab, let's have a look under the hood at data collection.

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Data Collection

Over 40 billion records a day are processed from millions of connected vehicles, forming the richest telematics dataset in the world consisting of engine data, GPS data, accelerometer data, and more.

Our rich and large datasets are vital to provide the best data services to our customers. The volume of data is important when conducting machine learning algorithms. The more data we have, the better and more accurate our algorithms can be. They are "rich" because only 10% of the data we collect is traditional telemetry data corresponding to GPS location and speed. Going well beyond the traditional dataset, we have the capacity to offer powerful data services related to engine diagnostics, accidents events, fuel consumption and more.

A graphic showing a car with information such as location, speed, and engine reports funneling into it.
A graphic showing a database, a lock, and a symbol of the earth.


The data from the Geotab telematics devices is securely sent to our gateway servers over a cellular network and is then piped into our data environment in Google BigQuery. This gives us the power to look anonymously at data across all vehicles from one central location. On average, there is only a 5-10 second delay from the time the telematics device logs a record, until the time it reaches our data environment. Pretty impressive for over 2 billion records a day!


Data is not powerful until it is enriched. We enrich this data by combining it with secondary data sets, aggregating it to preserve customer privacy and running machine learning algorithms on it using powerful tools like scikit-learn and Tensorflow. Using tools like Dataflow and Kubernetes, we transform multiple streams of data into datasets that can then be used to extract valuable, meaningful, actionable insight that can be then be developed into a tangible solution.

A graphic showing a computer with data streaming out of it.
A graphic showing a mobile device with a map as well as some weather information.


From our enriched data, we then produce data solutions that our customers and partners can readily use. Data solutions can range from giving our developer community the power to access industry benchmarks for safety to providing customers with Intelligence Data that can help drive smart city initiatives (datasets like hazardous driving locations, road impediment data, and more).

Data Insight Reading

Looking for guides and resources to help understand the value of big data? You've come to the right place.

Performance Benchmarking with Big Data

The value of big data lies in how well an organization is able to draw insight from data and turn it into measurable revenue generation or cost savings. Discover how with benchmarking data.

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Big Data and the Smart Fleet Revolution

Discover how the smart fleet movement is happening now. The Internet of Things (IoT) is expanding rapidly, and this includes increasing connectivity in the automotive realm.

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Are You Getting the Most out of Your Data?

Data is increasingly important to business in every industry – especially fleet management. Learn how telematics comes into play and how you can get the most from your data.

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