Hadoop: The funny name for serious big data

Big data means big opportunity

In an economy still recovering from the Great Recession, growing industries are important to nurture and pay attention to. For those looking for work, this has never been more true. Just as big data becomes more intelligent and efficient, so do the methods for gaining employment in the future workforce that big data is creating.

Companies like SimpliLearn are racing to offer cost-effective courses that provide continuing education to technology professionals and motivated entrants into the big data revolution. As quickly as information seems to be made obsolete by new technological advances, it makes sense to minimize the financial investment required to get up to speed.

In fact, in this writer's opinion, it just makes sense that learning about how the Internet of Things and big data can intersect to make our lives better takes place online.

But what the heck is Hadoop?

No, it isn't a town in India. Although, I'm sure if there is a town called Hadoop, it will soon be improved by the big data revolution underway in the tech sector that impacts our daily lives. Hadoop is about removing many of the constraints associated with handling and process the information known as big data.

Like the name implies, big data can be very, very big. Hadoop empowers computers to reach beyond their physical limits and manage data from a variety of sources without requiring a traditional server infrastructure. For computers, this means that the size of a hard-drive or the amount of RAM available to facilitate processing of data isn't necessarily a hard limit for the amount of information that can be processed.

Working together to answer the big questions

Hadoop breaks information apart and allows the workload to be spread across a variety of computers through the Apache Project's efforts to create a free, java-based network solution for big data. The real genius in Hadoop's approach to managing information is that it gets around the traditional bottlenecks experienced by servers transmitting information.

Imagine that instead of waiting for huge files to be transferred to your computer, you can transfer the comparatively small process of processing the data to where the information is currently stored. That, in a nutshell is how Hadoop helps make data processing easier. For big data, the size of the file being transmitted back and forth between machines and servers is incredibly important. If you can break free of the bandwidth constraints that make handling big data a pain, then you've made a big step in the right direction towards making information more accessible; especially for portable processing systems.