Introduction to Big Data and Hadoop

Big data is a collection of large datasets that cannot be processed using traditional computing techniques. It is not a single technique or a tool, rather it has become a complete subject, which involves various tools, techniques and frameworks. Big data involves the data produced by different devices and applications. Given below are some of the fields that come under the umbrella of Big Data.

Big Data is a term for collection of data sets so large and complex that it becomes difficult to process using hands-on database management tools or traditional data processing applications. Let us talk more about this in this article on Introduction to Hadoop.

Big Data has now become a popular term to describe the explosion of data and Hadoop has become synonymous with Big Data. Doug Cutting, created Apache Hadoop for this very reason. Hadoop has now become the de facto standard for storing, processing and analyzing hundreds of terabytes, and even petabytes of data. Hadoop allows distributed parallel processing of huge amounts of data across inexpensive, industry-standard servers that store and process data.

Networking Due to the advent of new technologies, devices, and communication means like social sites, the amount of data produced by mankind is growing rapidly every year. The amount of data produced by us from the beginning of time till 2003 was 5 billion gigabytes. If you pile up the data in the form of disks it may fill an entire football field. The same amount was created in every two days in 2011, and in every ten minutes in 2013. This rate is still growing enormously. Though all this information produced is meaningful and can be useful when processed, it is being neglected.