How Become a Hadoop and Big Data Developer for Programmer


Fortunately, we have solutions. This article will provide you with all the information you require regarding Hadoop certification and landing that coveted Hadoop Developer job of your dreams! Even if you already work as a developer and have no plans to leave the field, you can benefit from upskilling nonetheless. Consider adding a certification in Hadoop to your CV.

What Exactly Is Hadoop?

Here are the basics: Hadoop is a framework that allows for the distributed processing of huge data sets across clusters of computers using simple programming models," according to the developer's website. As many as thousands of machines can be used, each providing their own computation and storage."

Open-source software utilities that are designed to work across a network of computers to solve problems associated with enormous amounts of data and computation are included in the collection. As a result, it's a great tool for dealing with the avalanche of information that comes from Big Data and developing practical solutions based on that data.

What is a Hadoop Architect's Role?

It's all about Big Data. As a result, Hadoop architects are becoming increasingly important as a bridge between companies and technology. It is their job to plan and design new big-data systems and to manage large-scale Hadoop applications development and deployment. Hadoop architects are among the highest-paid IT professionals, earning an average of $91,392 to $133,988 per year and up to $200,000 per year on average.

Understanding the needs of IT organizations, the workings of Big Data specialists and engineers, and how to serve as a bridge between these two critical entities is essential if you want to work in this field in the future

A Big Data Architect is essential for any organization looking to implement a Hadoop solution, as they can oversee the entire solution lifecycle, from requirements analysis to platform selection, technical architecture, application design and development, testing, and deployment are all part of the process.

Check to See If You Fulfill These Essential Prerequisites

However, businesses and organizations may place more or less importance on any one of the following skills when hiring a Hadoop Developer. The following is a list of competencies for Hadoop developers. Even so, you don't necessarily need to be an expert in every one of them!

  • Hadoop and its appropriate components must be understood as a requirement (e.g., HBase, Pig, Hive, Sqoop, Flume, Oozie, etc.)
  • Knowledge of back-end programming, with an emphasis on Java, JS, Node.js, and OOAD is a necessity.
  • The ability to write code that is efficient, reliable, and maintainable.
  • Writing Pig Latin scripts and MapReduce jobs
  • SQL, database structures, theories, principles, and practices are all well-understood.
  • Working knowledge of HiveQL is required.
  • Ability to analyze and solve complex problems, particularly in the context of Big Data, is a must.
  • An understanding of multi-threading and concurrency is a useful skill.

In addition, the number of companies turning to data architects (rather than data analysts or database engineers) to integrate and apply data from various sources will continue to grow. The ability to collaborate closely with end users, system designers, and developers will be an important part of your job as a data architect.

As a Hadoop Developer, What Are Your Responsibilities?

What exactly do Hadoop Developers do now that we understand the necessary qualifications? It is expected of a Hadoop Developer that they:

  • Ensure that all Hadoop applications are designed, developed, architectured, and documented.
  • Hadoop installation, configuration, and support are all your responsibility.
  • A scheduler can be used to manage Hadoop jobs.
  • Hadoop clusters and new clusters can benefit from MapReduce coding.
  • The detailed designs are derived from complex techniques and functional specifications.
  • It is necessary to design web applications that allow for fast data queries as well as fast data tracking.
  • Then, turn the reins over to the operations team and have them implement what you've learned.
  • Carry out software prototype testing and supervise the subsequent transfer to the operational team of the team.
  • Pig and Hive can be used to preprocess data.
  • Insure the confidentiality and security of the company's Hadoop clusters
  • HBase administration and deployment.
  • Analyze large amounts of data and draw conclusions from them.

As a result, the question of how much a Hadoop Developer is paid comes up frequently.

Is Hadoop Really That Big a Deal, Anyway?

Apache Hadoop, according to Datamation, "dominates the landscape" when it comes to Big Data tools. "100% of large companies" will adopt Hadoop, according to Forrester Analyst Mike Gualtieri, recently.

By 2020, a report from Market Research predicts that the Hadoop market will be worth more than $1 billion, a compound annual growth rate (CAGR) of 58 percent. Open-source Big Data tools are so important to IBM that it has hired 3,500 researchers to develop Apache Spark, a tool that is part of the Hadoop ecosystem.

Because of its ecosystem of open-source tools that aid in "highly scalable and distributed computing," Apache Hadoop has become synonymous with Big Data.

What Is the Pay for a Hadoop Programmer?

Hadoop has the most job openings in the Big Data field. By comparison, the average salary for Big Data jobs without Hadoop was $106,500 in 2013, according to Dice's survey of Hadoop professionals. The average salary for an entry-level Big Data Hadoop Developer, according to ZipRecruiter, is $112,000 per year.

The salary range for Hadoop-related jobs on Indeed ranges from $63,400 for an Administrator to $141,000 for a Software Architect.

There are Software Architects who make more than $141,000 a year, so keep in mind that those are the averages for those positions. It's a good start!

As a result of this generous inducement, the obvious question is:

How Do I Become a Hadoop Programmer?

This is where things get serious. To become a Hadoop Developer, what do you need to do first? When you consider the salaries involved, it's safe to assume this is a difficult field to break into.

The answer is no.

To begin, a degree in computer science is not required to work as a Hadoop Developer. Any degree in a related field, such as Analytics, Electronics, or Statistics, is acceptable. In theory, you can earn any degree you desire (Journalism, Art History, Medieval Basket-Weaving). However, your degree should have some connection to the IT industry.

You'll also want to make sure you have a good grasp of the skills listed above. Independent study (books, internet, videos) or formal education are both viable options for acquiring these abilities. Of course, familiarizing yourself with the fundamentals of Hadoop is a must. To move on to the next step, it should be simple to get your hands on the open-source framework and give it a try.

And the next step is to perform Hadoop-related tasks. To put it another way, it's all about practice. Playing around with data means getting your hands a little dirty, so to speak. Learn how to decode, analyze, and transform it to your liking.

Finally, you'll want to get some formal certification and training. There are numerous resources available to you online, and many employers prioritize candidates who have certifications. Fortunately, finding a good training/certification program doesn't require much searching; just keep reading to learn more!

What's The Best Way To Get There?

The best way to learn the ins and outs of a field and have your knowledge backed up by authoritative validation is to earn an accredited, globally recognized professional certification. in a technical and highly competitive field like Big Data and Hadoop

Big Data Courses equips you with the skills and knowledge you'll need to advance quickly in the field of Big Data Architect. Big Data Architects are in high demand, and this program is designed to meet their needs. Upon completion of the course, students receive a Master's certificate and 200+ hours of high-quality eLearning, as well as on-demand support from Hadoop experts, simulation exams, and a community moderated by experts.

On top of this article is an infographic that provides several paths to follow in your journey.

 

What Does Hadoop's Future Hold?

Allied Market Research predicts that by 2021, the global Hadoop market will be worth $84.6 billion. Hadoop is the fourth most sought-after technology skill for Data Scientists in the top 20 most sought-after technology skills for Data Scientists.

Why is there such a high demand for this product? It's because businesses are finally realizing that providing highly personalized service to customers gives them a distinct advantage in the market. The right product at an affordable price is important to customers, but so is the feeling that their needs are being met.

How does a business go about determining what its customers want? By, of course, carrying out market research! Marketing research also means that their digital marketing departments are inundated with reams of Big Data. Large amounts of data are efficiently processed by Hadoop is able to! With the help of this data, companies can better target their customers and deliver a personalized experience to each of them. Those companies that are able to successfully implement this strategy will be able to rise above the rest.

Due to the high demand for Hadoop Developers, the market will continue to grow in the near future. Using Hadoop, businesses can sift through the mountains of data and come up with new and creative ways to entice customers into their establishments. In the modern world, if you don't do so, you'll be out of business.

Choosing to work as a Hadoop Developer will put you in a field with a lot of potential. In the event that you're already working as a developer, you should seriously consider learning Hadoop. When applying for promotion or a new job, having a certification makes you stand out from the rest of the applicants. This makes you more marketable.

What's the Best Hadoop Training Out There?

1. Data Scientist with expertise in Hadoop and Big Data

The Big Data and Hadoop Developer certification course is the best place to start. Professionals will be able to take part in Big Data projects after taking this course. The course provides hands-on training in Big Data and Hadoop as well as projects that require the implementation of Big Data and Hadoop concepts.

MapReduce, HDFS, Pig, Hive, HBase, Zookeeper, Flume, and Sqoop are all covered in this course.

This course is a gold mine for software developers and architects, data scientists, business intelligence professionals, project managers, and anyone else interested in Big Data Analytics, including recent college graduates.

2. Scala and Apache Spark

What's the next step? Scala and Apache Spark. With this course, students will learn how to use Hadoop in real-time processing.

"Transformation" and "mapping" concepts are supported by Apache Spark, an open-source cluster computing framework When it comes to mission-critical server systems, Scala (or "Scalable Language") is the preferred workhorse language.

After completing this Apache Spark and Scala course, you will be prepared to move on to either MongoDB or Cassandra, two other NoSQL databases.

  • MongoDB: Among the many features of MongoDB are the ability to model, store, query, and share large amounts of data across various operating systems and platforms. NoSQL database is the most popular in the industry.

You'll learn how to write Java and Node JS applications that use MongoDB; learn how to replicate and share data so that you can optimize read/write performance; learn how to install, configure, and maintain a MongoDB environment; and learn about monitoring and operational strategies for MongoDB.

While learning how to create and manage different types of MongoDB query indexes, you'll also gain a better grasp on DB Notes management, replica sets, and Master-Slave concepts through hands-on practice.

MongoDB is a great tool for storing and processing large amounts of unstructured data.

  • Cassandra: The "master-and-slave" architecture of Apache Cassandra, an open-source distributed database management system, makes it ideal for cloud computing. Writing-intensive applications are best served by Cassandra.

Cassandra's greater scalability allows it to store petabytes of data without sacrificing performance. A single point of failure is avoided by carefully engineering the system to handle massive workloads spread across multiple data centers.

As part of a course on Big Data and NoSQL databases and Cassandra, students will learn about the fundamentals of Big Data and NoSQL databases, as well as how to set up and manage a database, as well as how to use the Hadoop ecosystem of products that are based on Apache Cassandra.

3. Apache Storm

Apache Storm is a real-time event-processing framework for handling large amounts of Big Data. Understanding Apache Storm's core concepts and architecture is essential for successful implementation. Apache Storm's plan installation and configuration is also required.

For those who are interested in learning more about real-time event processing and Apache Storm's Trident extensions, this course is for you. In this course, you'll learn about Apache Storm's grouping and data insertion features, as well as Storm's interfaces with Kafka, Cassandra, and Java.

4. Apache Kafka

The fact that Apache Kafka is a high-performance real-time messaging system capable of processing millions of messages per second distinguishes it as an Apache open-source project. To ensure high availability, it has a fault-tolerant distributed messaging system.

An understanding of Kafka architecture, installation, interfaces, and configuration is required prior to getting started.

Kafka is now the preferred messaging platform for processing Big Data in real-time, as more businesses around the world adopt it. By earning this credential, you'll be able to handle massive amounts of data like a pro.

5. Impala

This is the last of the Big Data Hadoop architect certifications that you will need to earn. An understanding of Apache Hadoop's SQL query engine, Massively Parallel Processing (MPP), can be gained through familiarity with the open-source SQL engine Impala. You will be able to understand Impala's place in the Big Data Ecosystem once you have earned this credential.

Impala's ability to query data in Apache Hadoop and skip the time-consuming steps of loading and recognizing data gives it an advantage over competing solutions. Databases, SQL, data warehouses, and other database programming languages will also be covered.

Conclusion

As a Big Data Professional, following this path will get you where you want to go. As you progress, you'll gain a thorough knowledge of the IT landscape and its plethora of technologies, as well as the ability to evaluate how these technologies interact with one another. Your learning curve will be steep, but perseverance and hard work will pay off in the form of a data architect position down the road.

This guide is for anyone who wants to become a Big Data specialist. If you're interested in a career in Big Data, this guide will provide you with information on the most current technologies, top companies hiring, the skills needed to get started, and a personalized path to success.


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