Benefits and Importance of Hadoop and Big Data

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. With an increase in the usage of the internet, the data captured by Google increased exponentially year on year. Many top notch platforms like Facebook, Yahoo, Google, Twitter, LinkedIn and many more are using Hadoop for storage purpose because Hadoop is known for storing a large amount of data quickly. 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.

 

Importance of Hadoop

Ability to store and process big data rapidly

 

With data volumes and varieties constantly increasing in today’s time, especially when there are so many users using the internet and social media. Having sound software that can authentically store huge data is a key consideration. Hadoop is specially designed for this purpose.

 

Computing power

 

Hadoop’s MapReduce takes a few minutes to process terabytes of data and a couple of hours for petabytes of data. The more computing nodes you use the more processing power you have.

 

Fault tolerance and Security

 

Security is the top priority for every organization. So when it comes to authentication and security, Hadoop provides an advantage over other software, the data and application processing protect against hardware failure. If a node goes down, jobs are automatically redirected to other nodes to make sure the distributed computing does not fail. Multiple copies of all data are stored automatically.

 

Flexibility

 

Hadoop framework is used by many businesses to derive valuable business insights from data sources such as social media. Moreover, it can be used for a wide variety of purposes and you can easily store as much data as you want and decide how to use it later.

 

Economical

 

Hadoop, the open-source framework is free and offers a cost effective storage solution for businesses to handle huge datasets. Hadoop is fundamentally designed as a scale-out architecture that can affordably store all of a company’s data for later use.  In an effort to cut costs, many companies are now adopting Hadoop and they prefer hiring individuals who have done Hadoop training in Delhi and have good knowledge about it.

 

Scalability

 

Hadoop is a highly scalable storage platform which can help grow your system to handle more data simply by adding nodes. Unlike traditional relational database systems (RDBMS) that can’t scale to process big data, Hadoop enables businesses to run applications on thousands of nodes involving thousands of terabytes of data.

 

Reliable

 

Reliability of data is one important thing that no business would compromise on.  Hadoop offers complete reliability in a situation where data loss happens on a regular basis, HDFS helps you solve the issue. It stores and delivers all data without compromising on any aspect, at the same time keeping costs limited. Whether you are a start-up or one of the top notches, Hadoop has proved its mettle when it comes to strong data reliability in a variety of businesses at full scale.

 

Improves speed

 

Hadoop is able to resourcefully process terabytes of data in just a while, and petabytes in hours. Its unique storage method is built on a distributed file system that fundamentally ‘maps’ data wherever it is located in a cluster. The frameworks for data processing are often on the same servers where the data is located, causing in much faster data processing.

 

Final word

 

The increased need to analyze, organize and convert big data into meaningful information is what has contributed to the popularity of Hadoop. Many individuals are today making efforts to join Hadoop training in Delhi owing to the reason that most of the companies prefer hiring individuals who have knowledge of Hadoop and big data.Learning Hadoop can give one the capability to deal with the complexities of high volume, velocity and variety of data; this is actually what is required today.

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