Perhaps the biggest challenge inherent in Big Data projects is ensuring that there are underlying tools and infrastructure components— whether on-premises, in the cloud, or even in the car—to store data in ways that make sense and that enable timely analysis of that data in order to turn it into information and, ultimately, action.
For decades, information experts have attacked this problem. In fact, our current efforts around data engineering can be traced back to the 1950s and 1960s.
In this paper, you will go on a journey of discovery. You will travel back to the early days of electronic data and trek through the decades all the way to today. Along the way, you will learn about the pioneers and products that have gotten us to where we are today.