Instructor-led Big Data Hadoop Certification live Online Training Schedule

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20,000.00 Duration: 35 Hours
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About your Big Data Hadoop Certification Training

Skills Covered

Distributed data storage and processing
Data analysis using Pig and Hive
Real-time data processing with Spark and Flink
Data ingestion techniques using Sqoop and Flume

Tools Covered

Apache Hadoop, HDFS, MapReduce, YARN
Apache Hive, Pig, HBase, Spark
Apache Sqoop, Flume, Flink, and Storm

Big Data Hadoop Certification Training Syllabus

Curriculum Designed by Experts

Introduction to Big Data and Hadoop
Topics
  • Concepts of Big Data and challenges
  • Overview of Hadoop and its ecosystem
Topics
  • Architecture of HDFS
  • Data replication and distribution
Topics
  • Principles of MapReduce
  • Developing MapReduce applications
Topics
  • Understanding YARN architecture
  • Job scheduling and cluster management
Topics
  • Introduction to Pig for data flows
  • Using Hive for data summarization, query, and analysis
Topics
  • Understanding HBase architecture
  • Integration of Hadoop with HBase
Topics
  • Basics of Apache Spark and its advantages over MapReduce
  • Building applications with Spark RDDs and DataFrames
Topics
  • Tools and techniques for data ingestion
  • Using Sqoop and Flume for data import/export
Topics
  • Introduction to stream processing
  • Basics of Apache Flink and Storm for real-time data processing
Topics
  • Optimizing Hadoop and Spark performance
  • Best practices for developing efficient data processing applications

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Why Big Data Hadoop Certification Training From Xpertised Learning

Live Interactive Classes

  • Top-Tier Trainers
  • Real Time Guidance by Industrial Experts
  • In Class Doubt Clearance

Resource Access

  • Life Time Access to Resource Library

Support

  • One-to-One Lab and Training Assistance
  • Help Desk Support
  • Doubt Clearance in Real-time

Project Based Learning

  • Labs and Learning Based from Industrial Experts
  • Learning Based on Project Scenarios

Certification

  • Xpertised Learning Training Certificate
  • Certificate of Completion

Labs

  • Cloud based Labs *Labs based on course requirement only

Big Data Hadoop Certification Training Details

This course delves into the principles of distributed storage and processing using Apache Hadoop and its components, such as HDFS, MapReduce, and YARN. It also explores other ecosystem technologies like Apache Hive, Pig, HBase, and Spark.

  • Gain expertise in big data technologies, particularly Hadoop, enhancing your ability to manage and analyze large datasets.
  • Boost your career opportunities by obtaining a certification that is highly regarded in the data science and analytics industry, making you a valuable asset to organizations.
  • Stay ahead in the rapidly evolving field of big data by mastering Hadoop, ensuring your skills remain relevant and in high demand.
  • Comprehensive knowledge of Hadoop architecture and ecosystem.
  • Hands-on experience with Hadoop tools and best practices.
  • Enhanced skills for data management, processing, and analysis.
  • Distributed data storage and processing
  • Data analysis using Pig and Hive
  • Real-time data processing with Spark and Flink
  • Data ingestion techniques using Sqoop and Flume
  • Apache Hadoop, HDFS, MapReduce, YARN
  • Apache Hive, Pig, HBase, Spark
  • Apache Sqoop, Flume, Flink, and Storm
  • To equip participants with the ability to design, develop, and maintain big data solutions using Hadoop and its components.
  • To prepare participants for the Big Data Hadoop Certification exam.
  • To provide hands-on experience in real-world big data projects.
  • IT professionals and software developers interested in Big Data technologies.
  • Data Analysts and Business Intelligence professionals looking to expand their skill set.
  • System Administrators and DBAs who need to understand Hadoop administration.
  • Basic knowledge of programming in Java is highly beneficial.
  • Understanding of Linux operating system basics for Hadoop configuration and operations.
  • In-depth understanding and practical skills in managing and processing data using Hadoop.
  • Techniques to analyze data efficiently with the use of Hadoop ecosystem tools.
  • Real-time data processing and analytics skills.
  • Access to a computer with a minimum of 8GB RAM (16GB recommended) for running virtual machines or Hadoop clusters.
  • A stable internet connection for accessing online resources and tools.
  • Opens opportunities as a Hadoop Developer, Data Analyst, Big Data Architect, and various other roles in data-intensive industries.

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