The Definitive Guide To BIG DATA HADOOP

by shivkumar singh Digital Marketing Executive

In IT Industry Big Data is the trending buzzword. Apache’s Hadoop is the most important Big Data platform which is been used by IT giants such as Yahoo, Facebook & Google. This step by step free course will help you become a Hadoop Expert. With an increase in the usage of the internet, the data captured by Google increased exponentially year on year.

Hadoop is a comprehensive package of open source project that offers a framework which is used to store a large number of datasets. Hadoop is provided for data storage, data access, and data processing and security operations. Hadoop is written in Java and is not OLAP (online analytical processing). It is used for batch/offline processing. Moreover, it can be scaled up just by adding nodes in the cluster. Hadoop skilled individual gets multiple benefits as one can get multiple job vacancies. Thus a big data Hadoop course is really very beneficial.

Characteristics of Big Data

(i) Volume – The name Big Data in itself is associated to a size which is enormous. Dimension of data plays a crucial role in shaping value out of data. Also, whether an exact data can actually be considered as Big Data or not, depends upon the volume of data. Thus, 'Volume' is one such factor that needs to be considered while dealing with Big Data.

(ii) Variety – The second aspect of Big Data is its variety.

Variety refers to heterogeneous sources and the nature of data, both structured and unstructured. During earlier days, spreadsheets and databases were the only sources of data considered by most of the applications. Nowadays, data is in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. that is being considered in the analysis applications. This variety of unstructured data poses certain issues for storage, mining and analyzing data.

(iii) Velocity – The word 'velocity' refers to the speed of creation of data. How fast the data is generated and processed to meet the demands, determines real potential in the data.

Big Data Velocity deals with the speed at which data flows in from sources like application logs, business processes, networks, and social media sites, sensors, Mobile devices, etc. The flowed data is immense and unbroken.

(iv) Variability – This refers to the inconsistency which is shown by the data at times, thus hampering the procedure of being able to handle and supervise the data effectively.

Summary

Big Data is defined as the data which is huge in size. Big data is just a common term describes as a collection of data that is huge in size and yet growing exponentially with time.
Examples of Big Data generation includes stock exchanges, social media sites, jet engines, etc.
Big Data is a mixture of components:

1) Structured, 2) Unstructured, 3) Semi-structured

Volume, Variety, Velocity, and Variability are few important Characteristics of Big data
Improved customer service, better operational efficiency, Better Decision Making are few such advantages of Big data