In recent years, there has been such a massive advancement in technology and data, that new roles have cropped up to accommodate the growing needs in the industry. The role of the Hadoop Administrator is one such trending job role in the Big Data domain. As the amount of data generated globally is increasing by the second, open-source data processing frameworks such as Hadoop are gaining immense traction in the industry.
Hadoop’s capacity to scale and process huge volumes of data has made it a trendy name in the tech field worldwide. The rising adoption of Hadoop across various parallels of the industry has further pushed the demand for skilled Hadoop Administrators.
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Who Is A Hadoop Administrator?
A Hadoop Administrator is an integral part of the Hadoop implementation process. Hadoop Administrators are primarily responsible for keeping the Hadoop clusters running smoothly in production. They administer and manage the Hadoop clusters and also other resources in the Hadoop ecosystem.
The role of a Hadoop Administrator is a customer-facing one. They are responsible for designing and formulating the architecture, development, and engineering of Big Data solutions of a company. They must also ensure that there are no loopholes in the installation of the Hadoop cluster for a company without any loopholes.
Apart from maintaining and monitoring Hadoop clusters, a Big Data (Hadoop) Admin must also be able to mitigate problems and enhance the overall performance of the Hadoop clusters.
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Skills Required to Become a Hadoop Administrator
Here’s a comprehensive list of all the necessary skills that a Hadoop Administrator must possess:
- Proficiency in Networking.
- Sound knowledge Unix based file system.
- Strong foundational knowledge of Linux OS.
- General operational expertise, including expert troubleshooting skills and a thorough understanding of the system/network.
- Experience with open-source configuration management and deployment tools (Puppet, Chef, etc.).
- The ability to install and deploy the Hadoop cluster, add and remove nodes, monitor tasks and all the critical parts of the cluster, configure name-node, take backups, etc.
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How To Become A Hadoop Administrator?
Becoming a Hadoop Administrator isn’t rocket science. Anybody who has a basic understanding of statistics, computation and popular programming languages is qualified enough to enroll in a Big data course and become a Hadoop Administrator. Taking up a big data course is essential because it gives you complete knowledge and not just hadoop.
After you complete a Big Data course, you will gain the following knowledge about hadoop:
- Have an in-depth understanding of the fundamentals of Big Data and how to handle and manage Big Data.
- Have a good understanding of security implementation and know the optimal techniques to secure data and the Hadoop cluster.
- Know how to leverage various Hadoop components within the Hadoop ecosystem.
- Know how to use cluster planning and tools for data entry into Hadoop clusters.
- Be proficient in operating and managing Hadoop clusters, right from installation and configuration to load balancing and tuning the cluster.
The best thing about big data courses is that the skills they teach aren’t limited to only a particular field in IT. Thus, apart from students aspiring to become Hadoop Administrators, IT professionals like Java Developers, Software Developers, System/Storage Admins, DBAs, Software Architects, Data Warehouse Professionals, IT Managers, and students interested in Hadoop cluster administration can also take up the big data courses.
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Future Scope Of Hadoop Administrators
Today, Hadoop has become synonymous with Big Data. Hence, companies all around the world are readily adopting Hadoop and Hadoop-based Big Data solutions, irrespective of their size.
Furthermore, due to the growing investment in Big Data and Data Analytics, the demand for professionals with Big Data skills is increasing as we speak. As more companies join the Hadoop bandwagon, they are creating the need for talented Hadoop Administrators.
In fact, “Hadoop Jobs” is one of the most searched terms on the leading job sites like Glassdoor, Indeed, etc. In light of this situation, anyone who has Big Data skills, particularly in Hadoop, is likely to see an ocean of opportunities open up before them.
If you are interested to know more about Big Data, check out our Advanced Certificate Programme in Big Data from IIIT Bangalore.
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Is Hadoop still in demand?
Without Big Data analytics, companies are blind and deaf in today’s time. Organisations have now realised the benefits of Big Data analytics which help them in gaining business insights and enhance their decision-making capabilities. It has been predicted that the market of Big Data will reach heights by 2027. Hadoop has come out to be a source of light in the world of Big Data analytics. The market prospects of Hadoop are great in various industries. Hadoop has emerged as a pioneering solution for processing and storing large amounts of data in different industry verticals. From industries like healthcare, education, finance, communication, retail etc., all have Hadoop applications running on them.
What is Hadoop, and what are its components?
Hadoop is a Big Data management framework utilising distributed storage and parallel processing techniques. The software is mostly used by Big Data analysts. Hadoop simplifies things and allows clustering multiple computers to analyse massive datasets rather than using one large computer to store data. There are three main components of Hadoop, including the Hadoop Distributed File system (HDFS), Hadoop MapReduce, and Hadoop YARN (Yet Another Resource Negotiator). These are categorised according to application, that is, HDFS is used for data storage, MapReduce comes in handy when there is processing required, and YARN takes care of all resources.
What are the advantages of using Hadoop as a software?
Hadoop has many pros. The data distributed over the cluster are mapped, helping a faster retrieval. The tools used to process the data are also often on the same servers that reduces the processing time. Hadoop is scalable, that is, a Hadoop cluster can be extended by just adding nodes in the cluster. It is cost-effective also as compared to the traditional relational database management system. Hadoop enables businesses to easily access new data sources and tap into different types of data to generate value from the data. It is also resilient to failure.