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 this white paper by analyst Charles Araujo from Intellyx.