Difference Between Big Data and Hadoop

Introduction

Big data is the concept which deals with the problems of data handling of a large volume of data. This concept plays a very important role in data analysis and handling data in an organization where a huge volume of data is required to be stored, handled properly for the analysis that could make the organizations able to plan their strategies more efficiently and this could help an organization to generate more profit.

Handling of Big Data

The huge amount of data which is handled and analyzed by the concept of Big Data is the data that has been generated by the sales, production, and marketing done by a company in a month or a specific time period and if data is handled by the concept of Big data than this could be very beneficial for their business.

For example, through the business process of a company there might be a need to put a lot of work into collecting thousands of pieces of data on purchases in currency formats, on customer identities like name or their ID number allotted by the government, or on product information that what model number has been bought by them. All of this, or any other large amount of information, is known as Big data.

Solve the Big data Problem with Hadoop

Hadoop works on big data in a predefined manner and gives the result by processing the data through the help of algorithms and methods. Hadoop is a very useful tool or software that provides with various components which make the work more efficient.

MapReduce: Hadoop includes the feature of MapReduce and Hadoop Distributed File System (HDFS). Both these features are very useful and work in their own way to make your work easy. MapReduce firstly maps a large amount of data and then reduce it to a small amount of content for specific results, this basically works as a filtering process of the raw material.

HDFS: HDFS system is then used to distribute the data over a network. Thus, the big data professionals can use the features of Hadoop to analyze the big data properly and this can also provide them with the best results for their business strategies.

Working of Hadoop

Hadoop works on a large amount of data in a way in which the data is processed in small packets or blocks and all the blocks are of the same size of 128MB starting from the first block to the second last block whereas the last block is of the comparatively small size of 6MB. These small packets contain the information of data within them and now they can be easily analyzed.

Advantage of Hadoop

As the Big data is of huge volume, fast velocity, and different variety of information or set of data that requires a special platform and techniques through which it could be handled and analyzed. Hadoop provides a great advantage over the traditional way of data handling as this software has various components and features which makes it very easy and beneficial for professionals of data handling to handle and manage a large amount of sorted and raw data to make it a simple and approachable data that could be further used by the professionals for the betterment of working of their organization.

Hence, Hadoop can easily handle Big Data and is a better way of handling and managing big data.

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