When Big Data

When Big Data, IoT and Geospatial Technology Collide

When Big Data, IoT and Geospatial Technology Collide

Geospatial intelligence is ingrained in our daily lives. We use map apps on our smart phones, companies use location-based beacon technology to target consumers, we use geo-tags with social media and we depend on a vast network of precision logistics to keep our lights on, our vehicles driving, our packages delivered and our cupboards stocked. The mechanism that supports all of these endeavors is rooted in the realization and virtualization of big data. If we needed an umbrella under which we would hang these concepts, we’d call it the Internet of Things – an amorphous framework that encompasses both legacy and leading edge technologies, big data, the literal Internet, and users spanning from industrial machines to the average consumer with a smart phone.

Despite the obvious need for geospatial data within this IoT framework, industries have found in calculating the value of that data to be a complex practice. Industries that once stood alone and operated in silos, have become interconnected by sheer necessity – collecting, analyzing, sharing and even selling data. It no longer is acceptable for companies supporting critical infrastructures to track basic data. They must gather data from all facets of operations and information technologies, analyze that data, and turn it into actionable intelligence. The value of data today truly exceeds its numerical quantity.

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Geospatial Data and the Internet of Things

Geospatial data is the key to unlocking some of the critical functions that developers and end-users require to effectively empower the Internet of Things. Navigation functions on a cell phone? Geospatial data. Restaurant or entertainment recommendations in a specific area? Geospatial data. City bus route coordination? Geospatial data. Most often, we see the end result of geospatial data virtualization, but what we don’t see is just how many people touch that data to even get it to the point of deployable information.

This Data Value Chain has changed the way people and groups of people interact in our daily lives, as a whole, both internally and externally. The industries affected by geospatial data use it in innovative ways – from the collection on the ground – to analytics in the back office. It drives decision-making, project management, business intelligence, and increases productivity by streamlining workflows. These industries are directly responsible for building and maintaining the critical infrastructure upon which cities – and countries – are built and maintained. With each iteration of geospatial data along the chain, the value of that data increases.

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The Data Value Chain is a framework in which people can view the flow of geospatial data from the instant it is collected throughout its entire lifecycle. Each vertical industry has its own flow (and needs) of data, but eventually, that data intersects with analytics engines that can turn individual points of information into all different kinds of actionable intelligence. The Data Value Chain depends on a blended technology ecosystem that acts as disruptive force throughout the global marketplace to root out traditional, static practices and supplant them with innovative, purpose-built solutions based on data analytics.

Technology is simply a means to an end. The focus should not be on the newest tools.

 



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