Course Details
This comprehensive course introduces you to the fundamentals of Big Data, Hadoop, and the rich ecosystem of tools that power distributed data processing. Ideal for aspiring data engineers, it blends theoretical concepts with hands-on practice to prepare you for real-world big data challenges.
Key Skills You’ll Gain:
- Hadoop Distributed File System (HDFS) – Learn how to store and manage massive datasets in a distributed environment
- MapReduce – Understand the framework for processing large-scale data efficiently
- Apache Hive – Use SQL-like queries to analyze structured big data
- Apache Spark – Perform fast, in-memory data processing for analytics
By the end of this course, you will have hands-on experience with Hadoop and its ecosystem, enabling you to design, deploy, and manage scalable big data solutions.
What You’ll Learn
This comprehensive course covers the fundamentals and advanced concepts of Big Data and the Hadoop ecosystem. Here’s what you’ll learn:
- Big Data Concepts – Understand the concept of Big Data and its five key characteristics: Volume, Velocity, Variety, Veracity, and Value.
- Applications of Big Data – Learn the importance and real-world applications of Big Data across various industries.
- Big Data Challenges – Explore the challenges in handling and processing large-scale datasets efficiently.
- Hadoop Framework Overview – Gain an overview of the Hadoop framework and its core components.
- HDFS Architecture – Understand the Hadoop Distributed File System (HDFS) architecture and its operations.
- Resource Management with YARN – Learn the role and working of YARN (Yet Another Resource Negotiator) in resource allocation and management.
- Hadoop Ecosystem Tools – Explore tools such as Hive, Pig, HBase, Sqoop, Flume, and Oozie for data processing and workflow automation.
- MapReduce Programming Model – Understand the MapReduce programming model and its execution process.
- Data Ingestion, Storage & Processing – Learn techniques for ingesting, storing, and processing data in Hadoop environments.
- Integration with Real-time & NoSQL Databases – Discover how Hadoop integrates with real-time and NoSQL databases for advanced data solutions.
- Future Trends in Big Data – Understand emerging trends and future directions in Big Data technologies.
Pro Tip: This course emphasizes practical, hands-on learning through real-world Big Data projects, preparing you for a career as a Big Data Engineer.
Course Content
Requirements
This course is designed to be beginner-friendly and is open to anyone,
regardless of prior experience or background.
Course Description
This course provides a comprehensive introduction to Big Data concepts, the
Hadoop framework, and its associated ecosystem tools. You will begin by
understanding the fundamentals of Big Data, its key characteristics, and its
growing significance across industries. The course explores the challenges in
managing large-scale datasets and introduces the Hadoop architecture,
including its core components such as the Hadoop Distributed File System
(HDFS) and YARN for resource management. You will learn how Hadoop
processes data using the MapReduce programming model and how various
ecosystem tools like Hive, Pig, HBase, Sqoop, Flume, and Oozie enhance data
storage, processing, and analysis. Additionally, you will gain insights into
integrating Hadoop with real-time processing systems and NoSQL databases.
By the end of the course, you will have a solid understanding of Big Data
technologies, enabling you to work effectively with large datasets and explore
emerging trends in the field.
Course Content
Our comprehensive curriculum is organized into core modules, designed to take you from foundational concepts of Big Data to mastering the Hadoop ecosystem and its advanced applications.
- Introduction to Big Data
- The 4Vs of Big Data
- Types of Big Data
- Appendix
- Introduction to Hadoop & the Hadoop Ecosystem
- Test Your Knowledge (5 Questions)
- Functions and features of HDP, IBM value-add components, and IBM Watson Studio
- Test Your Knowledge (5 Questions)
- Introduction to Apache Ambari
- Test Your Knowledge (3 Questions)
- What is Hadoop?
- Test Your Knowledge (4 Questions)
- Introduction to MapReduce processing based on MR1
- Issues with and limitations of Hadoop v1 and MapReduce v1
- The architecture of YARN
- Lab 1 – Running MapReduce and YARN jobs
- Test Your Knowledge (3 Questions)
- Nature and purpose of Apache Spark in the Hadoop ecosystem
- Test Your Knowledge (5 Questions)
- Characteristics of representative data file formats
- Lab 1 – Using Hive to access Hadoop/HBase data
- Test Your Knowledge (4 Questions)
- ZooKeeper
- Slider
- Knox
- Lab 1 – Explore ZooKeeper
- Test Your Knowledge (5 Questions)
- Flume and Sqoop
- Test Your Knowledge (5 Questions)
- Hadoop Security and Governance
- Test Your Knowledge (4 Questions)
- Stream Computing
- Test Your Knowledge (4 Questions)
- Final Exam (20 Questions)
- How to Claim your Certificate
Highlights of this Course:
Upon successful completion of the course, you will receive a Course Completion Certificate.
