When it comes to tracking and analyzing data, nothing is more noteworthy than what geospatial data sets are doing. In a nutshell, this kind of data identifies a geographic area and the characteristics of said location through lines, points, polygons or other complex 3D renderings.

Geospatial Data Sets

While this is most popularly used for maps, it is nevertheless an impressively powerful tool businesses would be remiss to ignore. Spatial data observations focus on locations.

Every city, every house, every tree has its own latitude and longitude coordinates. The two primary types of spatial data are vector and raster data in GIS. But what is the difference between raster and vector data?

When should we use raster and when should we use vector? Find out more on the spatial data models commonly used.

Vector Geodata

Vector geodata (in the computer graphics sense) can represent a map. Such vectors take the form of sequences of latitude-longitude or projected coordinate pairs representing a point set, a linear map feature, or an areal map feature. Such data consists of lists of specific coordinate locations, along with some indication of whether each is connected to the points adjacent to it in the list.

Raster Geodata

You can map data represented as a matrix in which each row-and-column element corresponds to a rectangular patch of a specific geographic area, with implied topological connectivity to adjacent patches. This is commonly referred to as raster data.

Raster is actually a hardware term meaning a systematic scan of an image that encodes it into a regular grid of pixel values arrayed in rows and columns. When data in raster format represents the surface of a planet, it is called a data grid, and the data is stored as an array or matrix.

Targeted Marketing

More so than ever before, companies are developing ad campaigns that are highly customizable to suit their various audiences. Places like Google AdWords give businesses the power to target specific zip codes and a radius around one point on the map at different points in the day.

Yet, even with such a high level of adaptability, this means nothing unless you know where your audience is. This is how geospatial data sets are revolutionizing marketing. They help you determine exactly where your audience lives and can even show their movement over the past few years, giving you the ability to plan marketing campaigns for the future.

Problem Solving

For more transport oriented companies, having complete map data on traffic patterns, construction and school times means you have a better hold on how to navigate the area without delaying package delivery. Before this, delivery times were based on days. Now, companies are starting to predict closer to the actual time you should expect to receive your delivery, increasing customer satisfaction. This similarly opens the door to customer involvement. Better transportation means customers can request when a package is delivered so there are fewer missed deliveries, upping effectiveness of your services.

Predicting Growth

Business acumen is equal parts addressing the now as it is planning for five years down the road. In earlier years, this meant relying on internal trends collected and shared solely within the company, leaving smaller brands with little to do but hope for the best. Now, with years of data sets simply waiting to be downloaded, even the newest can foster a fighting chance. By studying geospatial data sets of population growth and distribution over the years across whatever city the business is located, you can more accurately predict up and coming areas or regions that look promising for expansion.

The practice of studying geospatial data sets is still in its infancy. There are no hard and fast rules, but there are infinite possibilities. Currently there are theories floating around about how best to use it, but the ideas are truly only limited based on you and your team. Spend some time coming up with various data set correlation possibilities that would help you capitalize on your specific services. Right now, the internet is swimming in free data, waiting for companies to jump in and take advantage of it.

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