Foundations of Apache Cassandra Training

Overview

This beginner-friendly course introduces core concepts of Big Data, NoSQL databases, and Apache Cassandra. Learn what makes Big Data powerful, explore analytics use cases, and understand how NoSQL differs from traditional systems. Get hands-on with Apache Hadoop and various NoSQL types. Then, dive into Apache Cassandra and its key features, architecture, read/write processes, data partitioning, replication, and network topology. Explore how it ensures fault tolerance and high availability. The course ends with a guided demo on setting up a virtual environment using VMware, PuTTY, and WinSCP. No prior experience is required. This course is ideal for students, developers, and aspiring database professionals. By the end of this course, you will be able to: - Understand Big Data and NoSQL fundamentals - Explain Cassandra’s architecture and operations - Set up a Cassandra environment using VM tools - Analyze data distribution and fault tolerance - Apply Cassandra in real-world NoSQL scenarios Ideal for data engineers, system architects, and IT professionals.

Syllabus

Big Data Concepts and Getting Started with Cassandra

Explore key Big Data and NoSQL concepts in this hands-on module. Understand what makes Big Data powerful, its analytics applications, and how NoSQL databases differ from traditional systems. Dive into Apache Hadoop and explore NoSQL types. Get introduced to Apache Cassandra with real-world examples, learn its strengths and limitations, and complete a guided demo on VM setup using VMware, PuTTY, and WinSCP.

Cassandra Architecture and Data Operations

Explore Apache Cassandra’s core architecture and data operations in this practical module. Learn how Cassandra’s architecture impacts performance, including its unique read and write processes. Understand data distribution through partitioning, replication, and network topology. Dive into fault tolerance mechanisms and examine how Cassandra handles various failure scenarios to ensure high availability and reliability.