Claudera Certified Developer for Apache Hadoop (CCDH)

What is HADOOP and why should you learn it?

In today’s industries, Hadoop is the best way to operate and manage Big Data, a huge amount of data by allowing many computers to do the entire work load. Hadoop is a software developed by Apache. It is an open-source structure that controls, stores and processes large amounts of data seamlessly, thus many IT giants like Google and Facebook, among others, are using Hadoop in their daily operations. Before getting into Big Data, Hadoop is considered as the fundamental foundation to many other succeeding processes. And as the core of other operations, knowing the principles, techniques and practices under its scope has been very essential with the emerging concepts and processes in IT industry. Obtaining a Hadoop certification would eventually bring an edge to your career and open your doors to the most in demand and highest paying jobs in the present times.

Can I possibly learn Hadoop with my current skills?

Individuals can definitely start learning Hadoop without restricting them with their current role or skill. Hadoop can be learned anew since training programs will provide learners with all of its fundamental concepts, Map reduce and Ecosystem. Thus, you will be able to understand, adopt and adapt on its language. Being a professional programmer is not a requirement, but to obtain a clear certification and to get a better understanding on the basic knowledge of Java or any other Object Oriented Programming (OOP), language is highly recommended.

Why do I need to take a course?

There are a lot of companies that offer training programs designed for CCDH certification, and such course is concentrated to equip participants with all the required knowledge, skills, experience and practices set to take their exams and to further their career opportunities. But above all, securing your course training for CCDH helps you reach certification level of expertise more smoothly.

Most individuals repel taking a course due to financial concerns, on a very limited training schedule. But measure the Return On Investment (ROI) for this coursework. Knowledge, certification, and higher pay scales would remain in you forever, with just a one-time investment. Consider taking a course as one of your best investment to brighten your career opportunities.

By taking a course, you will be prepared to earn the certificate. This could eventually open your doors to the most in demand IT jobs in today’s cutthroat market. With the growing IT industries and service, right now is the perfect opportunity for you to enter the field of Big Data or to become a Hadoop developer, Hadoop administrator or Hadoop data scientist. The associated learning found in MITS’ coursework is fundamental to every career path and very essential to reach your ultimate goal.

Why do you need to certify?

The fundamental purpose of any professional certification program is to offer an independent, dependable assessment of the knowledge and skills comprehension required for having an edge in performing a professional role. This assessment, like any other, is typically accomplished by the successful completion of the given examination.

What will happen if you get a CCDH certificate?

Possessing the CCDH certification demonstrates your technical knowledge, skills, and abilities to create, manage and maximize Apache Hadoop development projects. Becoming a Claudera Certified Hadoop Developer proves your understanding of applying Hadoop Distributed File System (HDFS); configuring, submitting and controlling jobs; Hadoop data types; algorithms and design patterns; and using of the Hadoop ecosystem.

What should you expect in a CCDH certification exam?

All participants who wish to earn the CCDH certification must pass the examination. The Claudera CCDH exam will test your knowledge of the principles, skills and practices required in the following areas:

  • Core Hadoop concepts
  • Storing files in Hadoop
  • Job configuration and submission
  • Job development environment
  • Input and output system
  • Job lifecycle
  • Data processing
  • Key and value classifications
  • Common algorithms and design patterns
  • Hadoop ecosystem


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