Apache Cassandra is an open-source, distributed NoSQL database designed for handling large amounts of data across multiple data centers with high availability, fault tolerance, and scalability.
It excels in use cases requiring low-latency data access and horizontal scalability, making it a preferred choice for industries like finance, e-commerce, and IoT, where real-time processing and high uptime are critical.
Learning Apache Cassandra is important for big data professionals, as it is widely used for managing large-scale applications, event logging, and time-series data.
A tutor can accelerate your learning by offering a structured curriculum, hands-on exercises, and real-world examples to help you master Cassandra's architecture, data modeling, and querying with CQL (Cassandra Query Language), preparing you for roles like Database Administrator or Big Data Engineer.
Chapter 1: Introduction to Big Data and Distributed Systems
Lesson 1: What is Big Data? Understanding Its Impact
Lesson 2: Challenges of Big Data: Volume, Variety, Velocity, and Veracity
Lesson 3: Introduction to Distributed Systems and Their Role in Big Data
Lesson 4: Overview of Big Data Tools: Hadoop, Spark, Cassandra, and More
Lesson 5: Comparing Apache Cassandra with Other Big Data Tools (Hadoop, MongoDB, HBase)
Chapter 2: Introduction to Apache Cassandra
Lesson 1: What is Apache Cassandra and Why Is It Important?
Lesson 2: History and Evolution of Apache Cassandra
Lesson 3: Key Features of Apache Cassandra
Lesson 4: Cassandra's Distributed and Decentralized Architecture
Lesson 5: Use Cases of Apache Cassandra in Real-World Applications (IoT, Financial Services, Social Media)
Chapter 3: Setting Up Apache Cassandra
Lesson 1: System Requirements and Prerequisites for Cassandra
Lesson 2: Installing Apache Cassandra on Local and Cluster Environments
Lesson 3: Configuring Cassandra for Single Node and Multi-Node Clusters
Lesson 4: Setting Up Cassandra on Cloud Platforms (AWS, Azure, GCP)
Lesson 5: Integrating IDEs (Eclipse, IntelliJ, Visual Studio Code) with Cassandra
Chapter 4: Cassandra Data Model and Architecture
Lesson 1: Understanding Cassandra's Data Model (Keyspaces, Tables, Rows, Columns)
Lesson 2: Partitioning and Clustering in Cassandra
Lesson 3: Consistency Levels and Their Impact on Data Availability
Lesson 4: How Cassandra Ensures High Availability and Fault Tolerance
Lesson 5: Introduction to Cassandra’s Architecture (Nodes, Data Centers, Clusters)
Chapter 5: Cassandra Query Language (CQL)
Lesson 1: Introduction to Cassandra Query Language (CQL)
