Hadoop Certification Guarantee for a Safe and Bright Career! By vinket

9/10/2019 Education ≈ Continuing Education

The advent of big data has created challenges for Data process and storage. The massive rise in the number of users of social media has accelerated the flow of information at a tremendous rate. The data flow and its storage have become challenging with the use of conventional methods. Hadoop was introduced in the market into store data storage and process obstacle that companies were facing. To get an insight into Hadoop, we need to understand big data first.

What is big data?

Big data encompasses dealing with large sets of data that are critical to the process and analyze systematically. It includes extracting useful information. It comprises oceans of data generated from various sources in a structured, unstructured and semi-structured format.  The use of conventional stools and techniques fails to process such large datasets and thus emerges the need for advanced technologies such as Hadoop to store, process, analyze data, and draw useful information.  In the present time, data is generated from online transactions, social media platforms, and other sources.  It facilitates the enterprises to arrive at better decisions and prepare strategies to stay ahead in the competition.


Big data is attributed with the following characteristics.

  • Volume:  The magnitude of data highly effects in determining the value of data. It is of the volume of information and datasets that it is categorized as big data. It is one of its attributes, and this data comes mostly in an unstructured format. This data can be from clickstreams on webpages, social media data feeds, clicks from web apps, and many more.

  • Variety:  In an enterprise, data emerge from various sources. It can be structured and unstructured format. In the conventional format, the data appeared in the format of spreadsheets and documents, unlike now, which is in the format of images, emails, videos, and many more. The variety of data poses numerous challenges that range from storage, preprocessing, and so on.

  • Velocity: It represents the speed at which data is received. The data is generated from various resources. As the data streams, it requires real-time evaluation and actions.


Need for Hadoop 

To counter the emerging needs for processing and managing big data. In the primitive ways, tools were used to store data and gain useful insight, but with the advent of big data, enhanced means for the big data needs are required, Thus Hadoop here comes into existence, it caters to the present market needs and provide framework to find the usable information by segregating data into large blocks and distribute into nodes in cluster.  It is designed with the vision that fault occurrence is common, thus in case of any failure. It is handled by the framework by transferring the data to other nodes in the cluster. Today organizations are hiring Hadoop professionals to meet the increasing requirements of data handling and data analysis.


Introduction to Big Data Hadoop

Hadoop is an open-source framework to store and process big data in the distributed matter on the clusters.  It is a top priority for most organizations. It is licensed under the Apache foundation.  It was developed by Dug Cutting and Michael J. Cafarella on paper issued by Google on MapReduce. This framework is written in Java programming language.


Core Components of Hadoop

  • Hadoop Distributed File System: It is a single storing unit in the Hadoop system; it authorizes the Hadoop framework to store data into multiple nodes in the distributed system. 

  • Hadoop Yarn:  In this component, all the processing activities of Hadoop takes place. It is used for resource management. It manages the resources in the clusters and responsible to schedule tasks in the applications. It constitutes the resource manager and node manager. 

  • Hadoop Common: All the system libraries and utilities required in the Hadoop system are contained in this component. 

  • Hadoop MapReduce: It is used for processing and enables a framework for hassle-free writing of applications for processing massive amounts of data in a reliable and fault-tolerant way. It breaks the task across processors.


 Top reasons to learn Hadoop for building career

The Big data market is on the way for massive evolvement without any signs of coming down. To learn Hadoop with Big Data Hadoop training can transform your career and make candidates opportune to construct a successful career. Here are the reasons for learning Hadoop for Big data.


  • Rise of Big data market:  Big data is a game-changer for major industries and creating opportunities for individuals skilled in the big data handling tools such as Hadoop and spark. It has created an enormous skill gap in the market. Hence the buzz for Hadoop is apparent.


  • Ascending career opportunities: Big data is one of the prominent technology in the market. Hadoop is a cost-effective and reliable technology to handle big data. Hence, there is a spawning demand for Hadoop professionals.


  • Higher salaries: Hadoop being the most commonly adopted framework to manage the process and analyze big data in the enterprises. But there is a huge lack of qualified and competent professionals in the marketing making enterprises pay more to the trained and experienced candidates.

How to become certified Hadoop professionals

Big data is a highly anticipated technology, to understand Big Data and Hadoop, it is necessary to gain knowledge from professionals. KVCH provides the best Big Data Hadoop certification training in Noida with in-depth insights and practical exposure. The course is imparted by professionally skilled mentors who train students on real-time projects for authentic industrial experience. We provide guaranteed placement assistance and a globally recognized certificate for making candidates more visible in the market.

About the Author

KVCH Content team are online media enthusiast and a blogger who closely follows the latest Career Guidance and Job trends In India and online marketing trends. We writes about various related topics such as Career Topics, Job Search and much more. 

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