Bump. Clank. Slosh.
Moving around a city or town in the early 1800s was a bit of a slow, messy slog. But nobody knew any better.
Then, in 1824, the city of Paris covered the Champs-Elysees with asphalt creating the first paved road, and kicked off a new movement that would transform cities around the world. By the late 1800s, cities around the globe were in the throes of a massive effort to pave their roads — and the impact to commerce and the quality of life was phenomenal.
But paving didn’t just transform the roads – it also transformed the nature of transportation itself as a paved road opened the door to a wholesale reenvisioning of how cities worked.
It may be shocking given the futuristic images it conjures, but when it comes to data science and the creation of intelligent, data driven applications, we are all living in our own dirt-road world.
And like the people happily, but slowly slogging along in the 1800s, we don’t know any better.
That’s all about to change.
It must.
Data has now become a vital business asset. Those organizations that can unleash its potential, rapidly and at scale, will have a tremendous advantage in a world in which data drives competitive value.
But to do so, companies must re-envision how they approach data, transform their static and slow-moving data pipelines into dynamic and real-time data science pipelines, and start creating a new class of intelligent applications.
It’s time to start paving some roads.
Read the entire White Paper here.
