The Big Data and Hadoop Administrator course will help you understand the basic and advanced concepts of Big Data. It prepares the participants for Big Data admin assignment. This course will take you through Hadoop’s Distributed File System, its processing and computation frameworks, Cluster Setup, Computational Frameworks, Ecosystem Components Services, and Hadoop Security. Master the various components of the Hadoop ecosystem like Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark. Get hands-on practice by implementing real-life projects in the domains of banking, telecommunication, social media, insurance, and e-commerce. Global Certify is conducting a 3-day comprehensive Big Data & Hadoop developer certification exam prep training course. Our quality courseware, interactive learning sessions with real-life examples and case studies. 3 months of Big Data & Hadoop developer Certification e-learning access will enable you to prepare confidently for the Big Data & Hadoop developer Examination to clear it on your first attempt. Take the first step towards exploring an opportunity to become a Big Data and Hadoop Administrator certified professional. Prepare for the Big Data and Hadoop Administrator Certification exam and fast-track your career as a Big Data and Hadoop Administrator certified professional.

• Data & Existing Solutions
• Welcome to the world of Big Data—What, Why & Where
• Case studies
• Hadoop & its Ecosystem
• Hadoop Core components
• Hadoop & its capabilities

• Gain knowledge on HDFS its internals, working & features
• Learn about possibilities without HDFS
• Differentiate or find similarities in different distributions of Hadoop.
• Identify the requirements to set up a Hadoop cluster

• The need for Cluster Management Solution
• Choice of Installation methods—Automated/ Manual
• Linux machines setup—Virtualization & Cloud
• Hadoop Cluster Setup—Apache Hadoop V2 & Cloudera Distribution of Hadoop (CDH)
• Cloudera manager features and capabilities
• Working with Hadoop cluster, HDFS & data
• Working with management console/ UI ( user interfaces) & Linux terminals
• Understand administration scenarios

• List and describe the files that control Hadoop configuration
• Explain how to manage Hadoop configuration with Cloudera Manager
• Locate configuration files and make changes
• Explain how to deal with stale configurations
• Explain the properties of addresses and ports of RPC and HTTP servers run by Hadoop Daemons
• Locate log files generated on hosts
• Filter information in log files
• Explain how to get diagnostic information from log files

• Explain how to add and remove nodes in an ad-hoc way
• Explain how to add and remove nodes in a systematic way, otherwise known as commissioning and decommissioning of nodes
• Explain how to balance a cluster
• List the steps for managing services including adding, deleting, starting, stopping and checking the status of services
• Explain the procedure to enable rack awareness
• List the steps to add, remove and move role instances and hosts
• Cite the challenges faced with the first version of Hadoop
• Explain the features in the second version that help overcome the challenges faced in the first version

• Describe the role of computational frameworks
• Explain MapReduce concepts
• Describe MRv2 on YARN
• Explain configuring and understanding of YARN
• Describe YARN applications
• Describe YARN memory and CPU settings

• Describe the scheduling concepts
• Indentify the Schedulers
• Explain the ways to manage resources using Schedulers
• Describe FIFO, Fair Scheduler, and Capacity Scheduler
• Explain how to configure Schedulers
• Explain queue management

• Planning Hadoop Cluster
• General Planning considerations
• Workload and cluster sizing
• Making Choices—Hardware, Software & Network
• Making Choices—Master/Slave considerations
• News from the world—Existing Setups

• Explain the concepts of Hadoop client, edge nodes, and gateway nodes
• Install and configure Hadoop clients
• Explain how Hue works
• Install and configure Hue
• Describe how authentication and authorization is managed in Hue

• Understand Data Ingestion & its types
• Knowing about various data ingestion tools & their capabilities
• Understanding how Flume works
• Understanding how sqoop works
• List some of the services and open-source components that work within the Hadoop ecosystem
• List the advantages and key features of Hive
• Describe briefly about the components of Hive
• Explain how to configure Hive in different modes
• Explain the architecture of HBase and cite the advantages of using HBase
• Explain the working of Apache Kafka
• Describe the architecture of Apache Spark

• Describe the different ways to avoid risks and secure data
• Identify the different threat categories
• Describe the security aspects for different nodes
• Describe operating system security
• Describe Kerberos and how it works
• Describe Service Level Authorization

• Describe cluster monitoring
• Describe the ways to choose the right monitoring solutions
• List the features and considerations of Cloudera manager for monitoring
• Describe the different categories of Hadoop Metrics
• List the different types of Hadoop Metrics
• List the steps to monitor a cluster by using Cloudera Manager