By:
Walter Scott, DigitalGlobe Founder and CTO
| 02.15.2017
Read Time:
4 minutes
In July 1995, a new online retailer called Amazon.com sold its first book. About a decade later, it eclipsed the dominant brick-and-mortar retailers on its way to becoming the place to buy books, and now, just about everything else. Building a wildly successful business of this type from the ground up took a lot more than simply having a cost-structure advantage over its competitors, as the burst of the dot-com bubble would quickly reveal.
To reach $10 billion in annual sales after its first decade in business mostly by selling a single product type – media – Amazon had to vertically integrate ordering, distribution, and retail analytics. It had to build a massive network of data centers and warehouses around the globe. It had to make the customer experience reliable and intuitive. And then Amazon realized that the enormous scale of its operations and the insight it gained in building it could be the foundation for a platform from which other businesses could sell their goods and services—or even, with Amazon Web Services, used as the foundation for their entire IT infrastructure. This idea helped the company reach $100 billion in annual sales after its second decade in business.
DigitalGlobe has been following this story very closely over the years, realizing that we have many elements in common with the incredible commercial ecosystem that Amazon created. In the same way that Amazon pioneered the infrastructure to support online bookselling, DigitalGlobe pioneered the infrastructure to support online, commercial use of high-resolution imaging satellites. We invested more than a billion dollars to build a global ground infrastructure to ingest, produce, and deliver enormous amounts of satellite data and information at great speed. We mastered the art and science of integrating data collected by different classes of satellites built by different manufacturers—both our own and others’. We listened to our customers’ needs and became deeply embedded in their workflows. And, like Amazon, we realized that we can best serve our customers by offering many different products from many different providers, along with a set of tools and APIs to enable them to be analyzed at scale.
Today, customers come to DigitalGlobe for the highest-accuracy, highest-resolution commercial satellite imagery that can be bought. But there are more commercial and open-source satellite and geospatial data sources than ever before, and that creates an opportunity to solve customer problems faster and more efficiently, and meet customer requirements that were previously infeasible. For example, DigitalGlobe recently partnered with South Korean satellite imagery provider SI Imaging Services to conduct an environmental impact analysis for a customer operating in a region with extensive cloud cover. Neither company could fulfil the customer’s imaging frequency requirements, but together, the whole was greater than the sum of its parts.
Further, trends in cloud computing and storage and data analytics have opened up a world of new possibilities for geospatial information to be applied to new problems in new ways. Today, there are more than 350 developers who are building new applications and machine learning algorithms on our GBDX platform, and our recently expanded Services business is adapting large scale analysis and algorithms to mission applications. The investment community recognizes the vast potential of our ecosystem as well. One of our many GBDX partners, SpaceKnow, recently announced a $4 million Series A funding round to expand its operations in the U.S., Europe, and Asia and further develop its Artificial Intelligence techniques for deriving economic indicators from our satellite imagery.
Like Amazon Web Services, which handles the undifferentiated IT heavy lifting for its users, GBDX handles the undifferentiated geospatial heavy lifting for our users, sparing them from the intricacies of data cleansing, normalization, and running geospatial algorithms at enormous scale. And we’re investing in initiatives like the SpaceNet Challenge, which is fostering machine learning innovation in the area of automated feature identification.
With the highest-quality imagery and other content, world-class platforms and infrastructure, deep geospatial knowledge, global distribution channels, and an ever-growing repository of analytic tools, DigitalGlobe has created the smartest, most comprehensive geospatial ecosystem on the planet – the DigitalGlobe. We invite geospatial content producers and consumers of all types to join us as we embark on the next era of understanding our changing planet.