The companies are revolutionizing at a fast pace delivering high-end products to their clients thanks to the emergence of big data. This is paving the ways for aspiring professionals wanting to make it in this arena. Though there are new career avenues awaiting skilled individuals, having mere knowledge about the big data technologies does not lead to anywhere. Certifications act as milestones in this case allowing the aspirants to prove their eligibility for vivid career profiles.
Cloudera certification is one of the similar kind designed especially for the Hadoop professionals. The success in big data field requires the people to clear these milestones in order to make a mark as a skilled big data individual.
Interested in getting Cloudera Certified? Check the Intellipaat Big Data Hadoop Certification training!
Watch this How To Become A Cloud Engineer for Beginners
What is Cloudera Certification all about and why should you clear it?
|Anybody can take||Yes|
|Visibility for Certified Professionals||High|
Cloudera certification exams comprise of hands on questions inculcating diverse technologies that go with or without Hadoop cluster such as Hive, Sqoop, Spark, Scala, SQL, Avro, etc.
It has been predicted that there will be a shortage of big data professionals in future across the world. This creates a huge skill gap to be filled with suitable professional having expertise in trending technologies. Clearing Cloudera certification will add a significant value to your resume making it more attractive and eligible for high-paying jobs in the domain of big data.
While Cloudera comprises of many types and levels of certifications, one of the most sought-after certifications is CCA-175 which is for Hadoop and Spark developers. CCA stands for ‘Cloudera Certified Associate’ which is an important step in the CCP (Cloudera Certification Professional) program.
Go through the Intellipaat Big Data Hadoop online training for clearing the Cloudera Certification Exam!
What are the skill sets that the CCA-175 Certification tests:
- Knowledge of Hadoop pillars – HDFS and MapReduce
- Writing MapReduce program in Java and others
- Deploying Hadoop clusters at scale
- Understanding Hadoop 2.0 YARN principles
- Big Data Analytics using Hive and Pig
Watch this Cloud Certification Training for Beginners
CCA-175: A continuous updated certification
In order to match the continuously upgraded trends in Hadoop and Spark implementation, CCA-175 mandates the certification holders to clear the test in every two years. This certification follows the following pattern for the exam:
Number of Questions: 10 to 12 questions.
Types of Questions: All are performance-based questions. The questions basically comprise of cases to be solved by developing codes in Python or Scala. Sometimes, a skeleton of code is provided to be completed by the candidates, however that code is just for the reference as the developer has to develop the codes from scratch.
Time Limit for the Exam: The time limit is 120 minutes for completing the entire lot of questions.
Minimum Score: The candidate should score minimum 70% to become a Cloudera certified Hadoop developer.
Evaluation of the Exam: The evaluation of the exam is done on the same day after completion as a scorecard is e-mailed to the candidate and a confirmation mail is sent to him after two days of the test.
Check the Intellipaat Hadoop tutorials to get ahead in your career!
How to prepare for CCA-175 certification exam?
Merely having theoretical knowledge is just not sufficient as a proper planning and management is very much needed to complete the test successfully within the time slot. Your preparation for the CCA-175 certification exam is incomplete without the following:
Hadoop Architect: Since this certification is all about Hadoop and Spark clusters, knowing the ins and outs of Hadoop architect will act as a leverage in scoring high. The candidate must have a grip on coding, debugging, YARN, MapReduce, etc.
Clear CCA-175 certification today by getting an industry recognized training on Hadoop Architect. Enrol Now!
Spark: The Spark use cases can be implemented in Python or Scala with the help of provided templates. Transferring the data to and from HDFS, joining disparate datasets, filtering the data into smaller datasets, etc., are some of the scenarios to be implemented using Spark. Hence a thorough grasp of Spark is a must to succeed in this test.
Hive: A basic knowledge about Hive and Impala will add a bonus point in score while solving the practical questions.
Avro Tools: Some of the questions may require the candidates to extract an Avro schema, create a table in Hive Metastore using Avro file format, evolve an Avro schema by changing JSON files, etc. Hence an aspirant should be proficient in Avro tools.
Sqoop: A good command over Sqoop is an important ingredient to succeed in this test. Some of the use cases on Sqoop include importing/exporting data from MySQL and changing the delimiter using Sqoop.
Time Management: The candidates are asked to develop codes for different use cases which takes more time than usual which may lead him only half way through. Rigorous practice and taking CCA-175 Simulator may help the candidate get a fair idea about the question patterns and time required to solve them.
How will CCA-175 help you achieve success?
You may be a master of Hadoop and Spark, but without a certification it is almost useless as the companies need proof of your skills. Cloudera provides you an opportunity to authenticate your knowledge by designing a specific certification CCA-175 that gives you a privilege over other developers. Being equipped with the knowledge about Hadoop and Spark administration will help you grab the high-paying career opportunities along with an expertise in a broad spectrum of technologies.
Hence CCA-175 is a stamp to launch your career into the big data space promoting your skills to the leading technology brands.
Get in touch with Intellipaat to take your career to the next level.
- Big Data Analytics Tools – Measures For Testing The Performances
- Hadoop Training- Virtual Classes for Big Data Management
- NoSQL vs. SQL – What is Better?