Why this course?

Description

In today’s Big Data world, traditional relational databases often fall short when it comes to handling large-scale, distributed, and high-velocity data. This is where Apache Cassandra, one of the most popular NoSQL distributed databases, excels.

This course, Apache Cassandra for Data Engineers, is designed to take you from the fundamentals of Cassandra all the way to hands-on data engineering use cases with CQL (Cassandra Query Language) and Apache Spark integration.

We start by exploring what Cassandra is, how it differs from traditional databases, and why organizations such as Netflix, Uber, and Instagram rely on Cassandra for high availability, fault tolerance, and linear scalability.

Next, you will get hands-on with:

• Installing Cassandra on Linux (Ubuntu).
• Learning and practicing Cassandra Query Language (CQL) to create, manage, and manipulate data.
• Working with keyspaces, tables, indexes, and functions.
• Performing DDL, DML operations, and advanced queries step by step.

 

After building a strong foundation in CQL, we’ll dive into Cassandra’s architecture, where you’ll learn how it distributes data across nodes, ensures availability, and maintains performance at scale.

Finally, you will learn how to integrate Cassandra with Apache Spark, a critical skill for Data Engineers working on large-scale data pipelines. You’ll practice reading and writing Cassandra tables directly from Spark, enabling advanced analytics and data processing.

By the end of the course, you’ll be able to: Understand and explain NoSQL and Cassandra fundamentals. Write, execute, and optimize queries using CQL. Design and manage keyspaces, tables, and data models.Grasp Cassandra’s distributed architecture and storage mechanisms. Build data pipelines with Cassandra + Spark for real-world applications.

This course is hands-on, beginner-friendly, and data engineering-focused, making it the perfect starting point for anyone looking to work with Cassandra in real-world projects.

What will students learn in your course?

• Understand the fundamentals of NoSQL databases and why Cassandra is used for Big Data applications.
• Install and configure Apache Cassandra on Linux (Ubuntu) for hands-on practice.
• Work with Cassandra Query Language (CQL) to perform data definition (DDL) and data manipulation (DML).
• Create and manage keyspaces, tables, indexes, and user-defined types.
• Write and execute queries for SELECT, INSERT, UPDATE, DELETE, and BATCH operations.
• Use functions, arithmetic operators, scalar functions, and aggregate functions in Cassandra.
• Gain in-depth knowledge of Cassandra’s architecture, including its storage engine, guarantees, snitches, and distributed design.
• Understand how Cassandra achieves high availability, scalability, and fault tolerance.
• Integrate Cassandra with Apache Spark to build real-world data pipelines.
• Read and write Cassandra tables using Spark for advanced analytics and data processing.
• Apply best practices for working with Cassandra in data engineering projects.

 

Who is this course for?

• Aspiring Data Engineers who want to build strong skills in distributed databases and hands-on experience with Cassandra.
• Database Administrators (DBAs) looking to expand beyond traditional RDBMS into NoSQL and Big Data technologies.
• Software Developers interested in integrating Cassandra with applications and understanding how it differs from relational databases.
• Big Data & Analytics Professionals who want to learn how Cassandra powers real-world, large-scale data platforms.
• Students & Beginners who want to start their journey into Big Data, NoSQL, and data engineering with step-by-step guidance.