Scalability

When you install infrastructures for big data on site, you must have done some analysis about how much data will be gathered, how much storage capacity is required to store it, and how much computation power is required for analysis purposes. Accordingly, you must decide on the hardware required in this setup. Now in future, if your data analysis requirement changes, you may start receiving data from more sources or need more computation power to perform analysis on it. In order to fulfil this requirement, you need more servers or for additional hardware to be installed in your on-site setup.

Another aspect will be this: let's suppose you did the analysis that you will gather this much data, but after implementation, you are not receiving that much, or before, you assumed that you would need this much computational power but now, after implementation, you realize that you don't. In both cases, you will end up with expensive server hardware of no use to manage. In a cloud setup, you will have the option to scale your hardware up and down, without worrying about the negative financial implications, and doing so is incredibly easy.

We will now move on to briefly discuss some of the key concepts and terminologies that you will encounter in your day-to-day life while working in the world of big data.