Hadoop has the capability to handle different types of structured and unstructured information, giving users a lot of flexibility for assembling

Every company has Big Data in its future and every company will eventually be in the data business – By Thomas H. Davenport.

In a fast-paced technology and programming world where more data is created every hour, organizations are realizing that categorizing and analyzing Big Data can help make major business predictions. This technological advancements and usage of smart devices in recent years has led to a data revolution. Currently, rapid data growth has led to a big hindrance in the computation process. Big Data requires higher computational power, where traditional data processors fail to deliver. To find a solution for this data processing problem, a program was needed which could answer all data related issues and this led to the introduction of a software platform — Hadoop.

What is Hadoop? 

Hadoop is an open source software platform that manages processing of data and storage for giant information applications running in clustered systems. It lies at the middle of a growing system of massive information technologies, which are primarily accustomed to support advanced analytics initiatives, as well as prophetical analytics, data processing and machine learning applications. Today almost every major digital enterprise has a Hadoop ecosystem to manage and store their data and drive applications such as search and profile sorting.

Hadoop has the capability to handle different types of structured and unstructured information, giving users a lot of flexibility for assembling; processing and analyzing information compared to relative information bases and data warehouses. Hence, Hadoop is helping us in solving problems usually associated with Big Data.

Previously our company’s data was stored in RDBMS (Relational Database Management System) and the problem of RDBMS was that it could not scale after a certain point of time. Hence, a Hadoop ecosystem (HBase, Phoenix, Hive, Kafka, Solr and Sqoop) emerged as the obvious solution for us. HDFS (Hadoop Distributed File System) is the storage layer of Hadoop which is very flexible and allows users to store any type of data.

The benefits extended by a Hadoop ecosystem

With 90 percent of data being unstructured and growing rapidly, an open source software platform is required to put the right Big Data workloads in the right systems and optimize the data management structure in an organization. The cost-effectiveness, scalability and systematic architecture make it even more pertinent for organizations to process and manage Big Data.

There are thousands of applications that push and pull data from Hadoop and run computations. Most of the services available in the ecosystem are to supplement the main four core components of Hadoop, which include HDFS, YARN, MapReduce and Common.

Hadoop’s quantum leap is a benefit that businesses and organizations can now find value in data that was considered useless as it allows enterprises to store as much data, simply by adding more servers to a Hadoop cluster. Each new server adds more storage and processing power to the cluster, which makes data storage with Hadoop less expensive than traditional data storage methods.

The problems associated with Hadoop and suggested solution

In today’s world, one of the biggest concerns revolves around the security and protection of sensitive information. Organizations are collecting, analyzing, and making decisions based on analysis of massive amounts of data sets from various sources, and additional layers of security of that data becomes crucial. The default Hadoop Cluster authentication is not secured as it is designed to trust all the user credentials provided, which can make it quite vulnerable. Kerberosed Hadoop Ecosystem provides a secure way to verify the identity of users.

Since its innovation in 2004, Hadoop has come a long way solving every specific problem. To help with its security database, Yahoo engineers set up to index the World Wide Web. Now, it has evolved into highly scalable, flexible Big Data programming software supporting all manner of data processing workloads and analytics-focused, data-centric applications.

The adaptability and future of Hadoop

In today’s world, Big Data is the new buzz word, and amongst this popularity, many organizations have started using Hadoop considering the scale of data that is generated is huge and is increasing progressively. The data generated every second around the globe is in terms of terabytes or petabytes and it is only going to grow in the near future.

However, the current scenario is that consumers demand quicker services and more bang for their buck. Customer care is all about personalizing services while working with different modes of consumer interaction and in the processing of data, Hadoop solves complex challenges faced by businesses. With this ecosystem, overcoming the shortcomings of traditional data approaches is common for Big Data technology.

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