The more we enter the digital world, the more we realize that Big Data and Hadoop solutions are becoming an essential part of getting the best out of enormous data. Businesses of all sizes are investing heavily on these two emerging technologies. In order to give you a complete view, we are giving you in-depth analysis of both of them and their correlation.
Big data is simply the large sets of data that businesses and other organizations put together to serve specific goals and operations. Big data can include many different kinds of data in many different kinds of formats. Take a look at the three properties that describe Big Data
Volume: The volume of the data should be very large, large enough that a single machine can’t handle processing this volume.
Velocity: The speed with which the data arrives is very high. One example being continuous streams of data from sensors etc.
Variety: Big data can consist of multiple formats of data including Structured, Semi-structured and completely unstructured.
You could say we leave digital footprints with everything we do on the internet and leave a digital trail. Different types of online activities such as uploading an image on the Facebook or posting your tweet on Twitter are adding up as a Big Data. It is assumed that by the year 2020 almost 1.7 megabytes of data will be created every second, for every person on earth. Big data can be analyzed for insights that lead to better decisions and strategic business moves.
Hadoop is based on the Google’s MapReduce framework designed to handle Big Data. Hadoop can be taken as a core platform for Big Data structuring and can be useful for analytic purpose. The current Hadoop ecosystem consists of the Hadoop kernel, MapReduce, the Hadoop distributed file system (HDFS) and a number of related projects. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Compared to traditional relational database management system that is quite expensive, Hadoop is open source and uses commodity hardware to store data so it really cost-effective. It was made available for public by Apache Software Foundation and the latest version 3.0.0 which is a Stable release came on December 2017.
These two technologies – both seeing rapid growth – are inextricably linked. From healthcare to IT firm, companies are using data-driven strategies to outsmart their competitors. For the digital success of any organization, both these technologies need to be explored properly. Hadoop's distributed computing model processes big data fast. Huge data found in Big Data require correct analysis via Hadoop. Both the platforms are inter-connected and can be used to gain maximum advantage.
Big data analytics offers a way to identify patterns and correlations in massive datasets and apply them to real-world problems.