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Cassandra Course Overview

Cassandra Course Overview

The Cassandra course offers a comprehensive dive into the world of distributed databases, specifically focusing on Apache Cassandra. This course is designed to equip learners with the knowledge and skills necessary to understand, manage, and effectively use Cassandra for scalable, high-availability applications.

Starting with Module 1, students are introduced to the basics of Cassandra, including its purpose, the CAP theorem, cluster architecture, and eventual consistency. This foundation is critical for understanding Cassandra's system requirements and setting up a lab environment for hands-on learning.

As the course progresses through Module 2 to Module 11, learners will gain a deep understanding of Cassandra's distributed nature, data modeling, and the intricacies of its data distribution mechanisms such as snitches, gossip, and virtual nodes. Practical skills in installation, configuration, and communicating with Cassandra using CQLSH are also developed.

Module 6 and beyond provide advanced knowledge, showcasing how to create applications with a Cassandra backend, perform data updates and deletions, manage a multinode cluster, and conduct monitoring and maintenance. Backup, restore, and performance tuning are covered in-depth to ensure that learners are well-prepared to handle real-world scenarios.

Throughout the course, key concepts such as secondary indexes, tombstones, hinted handoff, and data replication strategies are addressed, ensuring that students are ready to tackle Cassandra's complexities in production environments. This course not only imparts theoretical knowledge but also emphasizes practical application, making it a valuable asset for anyone looking to specialize in Cassandra.

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1,450

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Course Fee 1,450
Total Fees
1,450 (USD)
  • Live Training (Duration : 32 Hours)
  • Per Participant
  • Guaranteed-to-Run (GTR)
  • Classroom Training fee on request
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  • Live Training (Duration : 32 Hours)
  • Per Participant
  • Classroom Training fee on request
Koeing Learning Stack

Koenig Learning Stack

Free Pre-requisite Training

Join a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.

Assessments (Qubits)

Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.

Post Training Reports

Receive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.

Class Recordings

Get access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.

Free Lab Extensions

Extend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.

Free Revision Classes

Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.

Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

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♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

Inclusions in Koenig's Learning Stack may vary as per policies of OEMs

Request More Information

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Target Audience for Cassandra

  1. Koenig Solutions' Cassandra course offers comprehensive training on Cassandra's architecture, data modeling, and cluster management for IT professionals.

  2. Target Audience for the Cassandra Course:

  • Database Administrators (DBAs) interested in NoSQL databases
  • Data Architects designing large-scale, distributed data solutions
  • Data Analysts looking to understand Cassandra for big data analytics
  • Software Developers implementing applications with Cassandra as the backend
  • System Administrators responsible for maintaining database environments
  • IT Managers and Team Leaders overseeing database or big data projects
  • Cloud Infrastructure Engineers focusing on database deployments in cloud environments
  • DevOps Engineers involved in continuous integration and deployment processes that include databases
  • Technical Leads and Consultants providing expertise in database selection and architecture
  • Data Scientists requiring knowledge of Cassandra for data processing tasks
  • IT Professionals aiming to expand their skill set in NoSQL database technologies

Learning Objectives - What you will Learn in this Cassandra?

Introduction to the Course's Learning Outcomes and Concepts Covered

Gain comprehensive knowledge of Apache Cassandra's architecture, data modeling, and application development. Learn to install, configure, monitor, and maintain Cassandra clusters for high availability and performance.

Learning Objectives and Outcomes

  • Understand the fundamentals of Apache Cassandra, including its use cases and the CAP theorem.
  • Learn about Cassandra's distributed architecture and achieve proficiency in cluster setup and data distribution strategies.
  • Master the installation process of Cassandra and familiarize yourself with its configuration files and operational modes.
  • Acquire skills in using CQLSH for database interaction, including creating keyspaces, tables, and managing data.
  • Develop a deep understanding of data modeling in Cassandra to optimize database performance and queries.
  • Build applications with a Cassandra backend, leveraging drivers, and connecting to clusters from web pages.
  • Perform data updates and deletions efficiently, while understanding the implications of tombstones and TTL.
  • Set up multi-node Cassandra clusters, considering hardware choices, storage, and network configuration for production environments.
  • Monitor and maintain Cassandra clusters using tools like Nodetool, Jconsole, and OpsCenter, and learn to repair and ensure data consistency.
  • Execute backup and restore operations, understand performance tuning, and apply stress testing to ensure cluster robustness.

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