Career Advice
Top 10 Reasons To Learn Big Data Hadoop
The Big Data Hadoop market is going through an enormous evolution without any possibility of a decline in the coming years. Considering the current growth rate, it wouldn't be an exaggeration to say - Hadoop is an excellent choice. It could be a massive revolution between your present career and your desired career.
There are undeniable reasons to excel in Hadoop, but before we start to discuss the reasons let's gain some knowledge on Big Data.
Big Data: Defined
Everyone appears to be discussing big data, but what is big data? Big Data is a progressing term that defines a large volume of structured, semi-structured, and unstructured data that can be dug for information and adopted in machine study assignments and other applications projects.
Big data deals with huge and more complex data sets. These sets are so roomy that conventional data processing applications can't handle them. But these huge data sets can be used in addressing problems related to the business you were not capable of dealing with before.
The Three V’s
Usually, we differentiate big data using V’s: Volume, Variety, and Velocity.
- Volume:
Volume is the amount of data produced and stored. The volume of the data concludes the importance and possible vision and whether it can be treated as big data or not.
- Variety:
Variety refers to the kind of data that is available. It helps out the person who examines it to use the resulting observation efficiently. Data in the form of images, video, audio need extra processing to obtain meaning and backing.
- Velocity:
Velocity is the rate at which data is produced and handled to meet the needs and challenges.
How Is Hadoop Being Used in Big Data?
Hadoop, a distributed processing framework, is a source that controls the storage and processing of big data. It is the center of an expanding network of big data machinery that is mainly used to carry out an analytical program, involving projective analytics, machine learning, and data mining.
It can control various types of structured and unstructured data, providing users extra flexibility for analyzing, processing, and gathering data compared to data provided by data warehouses and related databases.
It was developed as an open-source project part of the ASF (Apache software foundation). Hadoop's commercial distribution is offered by four primary members currently named: Cloudera, Amazon web services, MapR Technologies, and Hortonworks. There are many other vendors like Microsoft, and Google, that offer cloud-based services that construct upon Hadoop.
Hadoop drives on a bunch of production servers and can level up to hold hundreds of hardware nodes and a huge volume of data. The distributed file system is used by Hadoop to provide quick data access over the nodes in a group, and additional fault-tolerant abilities for continuous running of application if an individual node breaks down. After Hadoop emerged in the mid-2000s, it became an opening data management stage for Big Data analytics.
Hadoop is the principal device for analytics uses. Its ability to store and process data of different types makes it the best fit for big data analytics operations as big data set includes not only a huge amount of data but also numerous forms of data.
How Have Companies Benefited by Using Hadoop?
With the development of social networking, traditional databases met some hard challenges due to their rigid design. These restrictions gave rise to a technology called Hadoop. Hadoop has priority over other technologies because of its low cost per byte, high bandwidth to back MapReduce, high data scaling and accuracy, and approach to all types of operation on structured or unstructured data.
Tech giants like Google and Facebook use Hadoop to process, store and handle their huge amounts of data. Hadoop has proven beneficial for many small and traditional companies as well.
Some of its other benefits are -
- Hadoop is an extremely scalable storage stage. It can stock up and share out large sets across thousands of low-priced servers that function in a parallel way which make it cost-effective. With this approach, you are capable of balancing raw data, and there is no need for removing it.
- Allows businesses to contact new data sources, which let them utilize data with various forms. Use of diverse data sets allows business to gain maximum advantages from broadly stretched out data. Example of this elasticity is Hadoop reaching Twitter, Facebook and other social platform for assembling a huge amount of new data.
- Hadoop's storing system uses tools that are present on the same server as of the data. It records data on a group in a server. It allows quick processing and speedy recovery of information.
- Hadoop is built with the fault-tolerance feature. It allows delivered data to replicate itself to other nodes in the group when data is delivered to a certain node in a group. So data delivered is somehow gets destroyed or lost, a copy is accessible on another node.
- Hadoop ensures complete security of the system. Security parameters applied by Hadoop work like a shelter against threats.
10 Reasons to Learn Big Data and Hadoop!
As the Hadoop market is undergoing exceptional growth and maintains to show an abrupt growth rate, it wouldn't be a hyperbole to say that Hadoop is a great option that is painful as well as expendable. Hadoop has also developed into a vital solution for big data.
Hadoop is gradually making a reputation for itself. If this isn't sufficient here are a few additional reasons for those who are looking forward to a career as Hadoop experts
- The cost-effectiveness and quick results contrast to traditional results are one of the few reasons after the extraordinary increase of the Hadoop market, and it is estimated to grow to a bigger level and has persuaded many sectors like retail sector transportation and BFSI.
- Hadoop is vital for big data and has been implemented by many companies to deal with big data accurately. It is crucial for individual and associated technologies to learn Hadoop to take your career forward.
- With the right talent and knowledge, you can always pursue a career in Hadoop. Popular job profiles in Hadoop along with their projected growth include:
- Data Scientists - 6.4%
- Analyst - 4.3%
- Visualizer and Architects - 4.1%,
- Business and Research Analyst - 4.3%.
- Professionals from diverse backgrounds can learn Hadoop. The requirement for Hadoop experts is growing across the world. By 2021, the Hadoop market is predicted to reach $84.6 billion, and its steady growth turned into tremendous opportunities for IT experts.
- Big data and Hadoop are linked together. At some point, every company has to tackle big data that raise the adoption of Hadoop.
- The demand for experts is much more than the availability and companies are set to pay higher packages to the expert developers.
- The shortage of experts has created a space between demand and availability. So it is the correct time to pursue your career in Hadoop.
- The requirement for Hadoop experts can be attributed to the popularity of technology these days. It is one of the best solutions for big data, and it has become the base for many big data technologies, producing job at a sharp rate.
- Hadoop is not only touching only one company but transforming many domains collectively. Companies can influence its potential to develop the business value.
- Since the past few years, the implementation of big data Hadoop has amplified across numerous domains. Hadoop is the primary priority for companies today. This does not doubt any person to see noise in the market to study Hadoop.
Who should learn Hadoop?
Individuals having an IT background generally prefer learning Hadoop. But having a software background is not mandatory. Professionals working in job roles like Architecture, Developers, Testers, Linux/Network/Hardware Administrator, etc. can learn Hadoop and take the next big leap in their career.
Prerequisites to learn big data Hadoop:
- Linux operating system: Hadoop is commonly installed on Linux operating system. So you are required to have basic knowledge of Linux commands, editors, etc. You should be capable of installing and uninstall Linux.
- Programming languages like Java and Scala
- SQL knowledge
There are important software packages like HBase, Pig, Apache Hive, which are used with Hadoop ecosystem and these serve SQL like queries for querying HDFS data.
Salary Trends
Hadoop has been a great option for professionals looking for a high-paying career. Average salary of a Hadoop developer is estimated at around $98,000; it is almost 95% higher than the average salary of all other job positions across the world. The highest salary package in job-related to Hadoop is $123,000 for a Hadoop administrator. In the coming years, skilled Hadoop professionals can expect an increase in salaries from $119,250 to $168,250.
In San Francisco, California, $139,000 is estimated as the average salary for Hadoop Developer and a Senior Hadoop Developer can earn $178,000 and more. Overseas Hadoop job market has also been a development in which India is at the top followed by Malaysia and China.
Hadoop is a platform that will expand too many folds in the coming years, and there is no possibility of a downtrend. If you are planning to learn Hadoop, it is the best decision for starting a promising career in the IT sector.
What Next?
By far, you have learned how learning Hadoop is a great career choice and how you can improve your salary prospects by mastering Hadoop. To validate your understanding of Hadoop, you can opt for a Big Data Hadoop certification training course which will help you learn all the topics from basic to advanced levels. While a certification is not mandatory, it will assist you in gaining the necessary skills by following an updated curriculum and the latest best practices of Big Data.
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