This Big Data and Hadoop Administrator training course will furnish you with the aptitudes and methodologies necessary to excel in the Big Data Analytics industry. With this Hadoop Admin training, you’ll learn to work with the adaptable, versatile frameworks based on the Apache Hadoop ecosystem, including Hadoop installation and configuration, cluster management with Sqoop, Flume, Pig, Hive, Impala, and Cloudera. You’ll learn Big Data implementations that have security, speed, and scale.
Why become Big Data Hadoop Administrator?
Professionals who are working in this field can expect an impressive salary, with the median salary for data scientists being $116,000. Even those who are at the entry level will find high salaries, with average earnings of $92,000.
What are the objectives of this course?
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.
What skills will you learn?
- Understand the fundamentals and characteristics of Big Data and various scalability options available to help block size manage Big Data
- Master the concepts of the Hadoop framework, including architecture, the Hadoop distributed file system, and deployment of Hadoop clusters using core or vendor-specific distributions
- Use Cloudera manager for setup, deployment, maintenance, and monitoring of Hadoop clusters
- Understand Hadoop Administration activities and computational frameworks for processing Big Data
- Work with Hadoop clients, nodes for clients and web interfaces like HUE to work with Hadoop Cluster
- Use cluster planning and tools for data ingestion into Hadoop clusters, and cluster monitoring activities
- resource manager Hadoop components within Hadoop ecosystem like Hive, HBase, Spark, and Kafka
- Understand security implementation to secure data and clusters
Who should take this course?
- Systems administrators and IT managers
- IT administrators and operators
- IT Systems Engineers
- Data Engineers and database administrators
- Data Analytics Administrators
- Cloud Systems Administrators
- Web Engineers
- Individuals who intend to design, deploy and maintain Hadoop clusters
What projects are included in this course?
Successful evaluation of one of the following two projects is part of the Hadoop Admin certification eligibility criteria:
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.
Working with Clusters
Demonstrate your understanding of the following tasks (give the steps):
- Enabling and disabling HA for namenode and resourcemanager in CDH
- Removing Hue service from your cluster, which has other services such as Hive, HBase, HDFS, and YARN setup
- Adding a user and granting read access to your Cloudera cluster
- Changing replication and block size of your cluster
- Adding Hue as a service, logging in as user HUE, and downloading examples for Hive, Pig, job designer, and others
For additional practice we offer two more projects to help you start your Hadoop administrator journey:
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.
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 deletions and to make critical data available to users/applications even if one or more of these clusters is down.
This self-paced course provides 180 days of access to high-quality, self-paced learning content designed by industry experts.