The Hadoop admin training enables you to work with the versatile frameworks of the Apache Hadoop ecosystem. This Big Data administrator course covers Hadoop installation and configuration, computational frameworks for processing Big Data, Hadoop administrator activities, cluster management with Sqoop, Flume, Pig, Hive, Impala, and Cloudera.
By 2023, the Big Data analytics market is expected to reach $40.6 Billion, at a compound annual growth rate of 29.7-percent. With the world embracing digitalization, Big Data has a promising future. Professionals with expertise in Big Data have a high earning potential.
Yes, we provide 1 practice test as part of our course to help you prepare for the actual certification exam. You can try this free Big Data & Hadoop Administrator Exam Practice Test to understand the type of tests that are part of the course curriculum.
The Simplilearn Big Data and Hadoop Administrator course will equip you with all the skills you’ll need for your next Big Data admin assignment. You will learn to work with Hadoop’s Distributed File System, its processing and computation frameworks, core Hadoop distributions, and vendor-specific distributions such as Cloudera. You will learn the need for cluster management solutions and how to set up, secure, safeguard, and monitor clusters and their components such as Sqoop, Flume, Pig, Hive, and Impala with this Big Data Hadoop Admin course.
This Hadoop Admin training course will help you understand the basic and advanced concepts of Big Data and all of the technologies related to the Hadoop stack and components of the Hadoop Ecosystem.
Successful evaluation of one of the following two projects is part of the Hadoop Admin certification eligibility criteria:
Project 1
Scalability: Deploying Multiple Clusters
Your company wants to set up a new cluster and has procured new machines; however, setting up clusters on new machines will take time. Meanwhile, your company wants you to set up a new cluster on the same set of machines and start testing the new cluster’s working and applications.
Project 2
Working with Clusters
Demonstrate your understanding of the following tasks (give the steps):
For additional practice we offer two more projects to help you start your Hadoop administrator journey:
Project 3
Data Ingestion and Usage
Ingesting data from external structured databases into HDFS, working on data on HDFS by loading it into a data warehouse package like Hive, and using HiveQL for querying, analyzing, and loading data in another set of tables for further usage.
Your organization already has a large amount of data in an RDBMS and has now set up a Big Data practice. It is interested in moving data from the RDBMS into HDFS so that it can perform data analysis by using software packages such as Apache Hive. The organization would like to leverage the benefits of HDFS and features such as auto replication and fault tolerance that HDFS offers.
Project 4
Securing Data and Cluster
Protecting data stored in your Hadoop cluster by safeguarding it and backing it up.
Your organization would like to safeguard its data on multiple Hadoop clusters. The aim is to prevent data loss from accidental deletes and to make critical data available to users/applications even if one or more of these clusters is down.
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