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Future of Internet Community

  • SkillRary SR
  • May 30, 2019
  • 0 comment(s)



In the past few of years, the two new terms which are most discussed in the internet community are– Big Data and Hadoop. This article helps readers to understand what the meaning of these two terms is, and how they influence the internet community not only in the present times but also in the coming future.


What is Big data?

Big data is a term that describes the large volume of data. It can be structured or unstructured. But it’s not the amount of data that’s important. But what matters is, what organizations do with this data. Big data can be analyzed for insights which lead organizations to take better decisions and also help them in making strategic business moves.


Making use of Big data

 We must understand that the importance of big data doesn’t lie in how much data you have, but it revolves around what you do with it. One can take data from any source and analyze it to find answers that enable

1) Reduction in cost.

2) Reduction in production time.

3) Development of new products.

4) Smart decision making.


Big Data Challenges

The major challenges which are associated with big data are as follows:

·         Capturing data

·         Storing data

·         Searching data

·         Sharing data

·         Transferring data

·         Analysis of the previously stored data

·         Presentation


But how to deal with such a large amount of data?

Google solved the problem of dealing with huge amounts of data, which was really a tedious task to process such data with the help of a traditional database server by using an algorithm called MapReduce. This algorithm divides the task into small parts and those parts are assigned to many computers which are connected over the network, and these computers collect the results to form the final result dataset



Doug Cutting, Mike Cafarella, and the team took this solution provided by Google and started an Open Source Project called HADOOP in 2005 and it was named after Doug son’s toy elephant. Now Apache Hadoop has become a registered trademark of the Apache Software Foundation.


The MapReduce algorithm is used by Hadoop to run applications, where the data is processed parallelly on different CPU nodes. In short, the Hadoop framework is capable of developing applications which are capable of running on clusters of computers and complete statistical analysis is performed for a huge amount of data.


It contains two modules:-

·         MapReduce

·         Hadoop Distributed File System (HDFS).


MapReduce: It can be understood as a parallel programming model used for processing large amounts of any type of data whether it is structured, semi-structured, or unstructured, on large clusters of commodity hardware


HDFS: Hadoop Distributed File System is also a part of the Hadoop framework, which is used to store and process the datasets. It provides a fault-tolerant file system to run on commodity hardware.


But why Hadoop is so successful?

The key to the success of Hadoop lies in the advantages it provides to its users, which are as follow-

·         Scalable

·         Resilience to failure

·         Cost-effectiveness

·         Fast flexibility


By looking at the technology and its reliability it can be easily said that Hadoop is the technology of the future and it will successfully simplify the process of storage and analysis of Big Data.


The global Big Data Platform market size was 41100 million US$ and it is expected to reach 86600 million US$ by the end of 2025, with a CAGR of 11.2% during 2019-2025.%.

[ref: ]


Data Science and Analytics professionals with MapReduce skills are earning $115,907 a year on average, making this the most in-demand skill according to the survey.  Data science and analytics professionals with expertise in Apache Pig, Hive and Hadoop are competing for jobs paying over $100K.



The fastest-growing roles are Data Scientists and Advanced Analysts, which are projected to see demand spike by 28% by 2020.



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