Regardless of whether you are at the office surfing the web, on the train reading the paper, or at home watching TV, I’m sure that at some time over the past month or so you have read or heard something about Big Data. It’s a buzzword that keeps popping up in our everyday lives, and maybe its got you thinking, “What is this big data that everyone is talking about and why is it such a big deal?” Well, before we answer those questions, let’s first look at what most companies are currently doing:
One Small Database For Man…
Any company that deals with the storage of information uses some form of database system, such as Microsoft SQL Server, PostgreSQL, Oracle, MySQL, and so on. These applications allow their users to capture, store, and analyze data with relative ease. But as one would expect, every business takes a different approach on how to handle their data. A corner store that’s logging a couple hundred transactions a day is obviously going to have different ways of dealing with their data, compared to an industry leading telematics company that collects millions of rows of GPS data everyday. Industries that deal with large data collection systems may take an approach like archiving, backing up, and/or replicating databases in order to preserve the data without slowing down production systems. However, these backups or archives aren’t always easily accessible, and when they are accessible, it can be painstakingly slow to run analysis on the database(s) due to the large quantity of data. So, how can companies utilize all their historic data without having to take more than half a day, or more, to run an analysis on it?
…One Big Data Leap For Mankind
Let’s take a step back and start with the basics: what is Big Data? Basically, big data is exactly as the name suggests – it is the collection of datasets that are so large and/or complex that the standard database systems have a difficult time being able to efficiently process the data. Big data systems are able to work with such large sets of data quickly and efficiently due to the advanced architecture and processing methods designed for these systems. An example of this is a method that was developed by Google called MapReduce. The way it works is that when queries are run on the large data sets, the queries are split and distributed across parallel nodes and are processed in parallel as well. The results from the parallel actions are then gathered and delivered to the end user.
To return to our question above, companies can use big data systems to not only provide storage of historical datasets, but also to give them the ability to run complex data analysis on their historical data. There are many different options when it comes to big data systems, from self-hosted to cloud based, and Google to Microsoft. There is something for everyone, just make sure you do your research about each provider and that you understand your company’s requirements before making a decision.
Geotab Takes on Big Data
There are hundreds of millions of data records that pass through Geotab’s servers everyday, including GPS data, engine data, accelerometer data, and more. Geotab has taken that leap forward and is diving into big data with some big ideas. Imagine selecting a route in MyGeotab to display on the map and being able to see the traffic flow rates for certain times during the day for that particular route. Or, what about being able to see an overlay on the map of cell network coverage based on the type of devices that are in your fleet. This way if one of your devices hasn’t updated recently you can quickly see on the map that they have entered an area with poor cellular coverage. The advantage of this coverage map is that it can be built from Geotab’s device logs so that the coverage maps are specific to Geotab devices and not generic maps provided by the cellular providers.
There are countless possibilities for Geotab as we start to dig deeper into big data and we can assure you that this data is going to be a big deal.
