[5 Ways] to Become a Certified Big Data Practitioner
In order to become a Certified Big Data Practitioner, you must first complete five different courses, each representing one area of expertise in the Hadoop ecosystem. These courses are offered through online platforms such as Coursera and edX, and they cover all sorts of topics like how to use Apache Hive or how to administer Hadoop clusters with Cloudera Manager. [read more]
read more: https://americanexponent.com/get-certified/
1) Join the Hortonworks Community Connection
In addition to the certification, there are many ways for you to join the Hortonworks Community Connection. You can start by subscribing to our blog, following us on social media channels, attending one of our events or even chatting with us on our forum. All of these are great ways to stay up-to-date on all things data and Hadoop.
read more: https://lucky13internship.com/introduction-2/
2) Use Cloudera's Learning Management System
Cloudera offers an online learning management system that is free for the first 60 days. Once you’ve registered, it takes just five minutes to learn how to use Cloudera’s Learning Management System (LMS).
1. Log in and click on the course you want to take.
2. Check out the course materials and videos (including slides).
3. Take quizzes and tests as you work through the material.
3) Use Hortonworks Data Platform
Hortonworks Data Platform is an open source enterprise data hub that enables enterprises to securely process, manage and analyze big data. Hadoop’s ecosystem of projects are all part of the HDP, from Hive and Pig to Tez and Spark.
4) Use MapR Converged Data Platform
MapR offers the Converged Data Platform, which is designed to simplify the data management process and provide practitioners with powerful tools for big data processing. It consists of MapR-FS, MapR-DB, MapR-ES, and MapR Control System.
5) Use Apache Hadoop
Apache Hadoop is an open-source software framework that supports distributed storage and processing of large data sets on computer clusters. To work with Hadoop, you need both the MapReduce and HDFS components. The HDFS component provides the file system where your data resides, while MapReduce is the programming interface you use to process this data. After downloading and installing these components, you can start working with them right away through their command-line interfaces or by installing one of many popular graphical interfaces.