Mastering Apache Cassandra: Key Skills for Data Engineers

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Programming Academy

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1 - Introduction

1 - Introduction.mp4

04:46

2 - What is Apache Cassandra.mp4

05:24

3 - What is NoSQL.mp4

01:46

4 - Can Relational Database work for Bigdata.mp4

04:55

5 - Tips to Improve Your Course Taking Experience.mp4

01:35

2 - Apache Cassandra Installation

6 - Installation Steps on Linux machines Ubuntu.html

3 - Cassandra Query Language CQL

7 - Data Types Part 1 Hands On.mp4

10:39

8 - Data Types Part 2 Hands On.mp4

06:00

9 - Data Types Part 3 Hands On.mp4

02:59

10 - UserDefined Types.mp4

04:25

11 - Data Definition DDL Create Keyspace Hands On.mp4

06:42

12 - Data Definition DDL USE Keyspace Hands On.mp4

02:45

13 - Data Definition DDL ALTER Keyspace Hands On.mp4

01:40

14 - Data Definition DDL DROP Keyspace Hands On.mp4

01:00

15 - Data Definition DDL CREATE Table Hands On.mp4

03:34

16 - Data Definition DDL ALTER Table Hands On.mp4

01:30

17 - Data Definition DDL DROP Table Hands On.mp4

01:41

18 - Data Definition DDL TRUNCATE Table Hands On.mp4

01:41

19 - Data Manipulation DML SELECT Statement Hands On.mp4

03:33

20 - Data Manipulation DML INSERT Statement Hands On.mp4

01:58

21 - Data Manipulation DML UPDATE Statement Hands On.mp4

01:35

22 - Data Manipulation DML DELETE Statement Hands On.mp4

01:19

23 - Data Manipulation DML BATCH Statement Hands On.mp4

02:19

24 - Arithmetic Operators Hands On.mp4

02:11

25 - Secondary Indexes Hands On.mp4

02:41

26 - Functions.mp4

00:47

27 - Scalar Functions.mp4

03:04

28 - Aggregate Functions.mp4

02:38

4 - Apache Cassandra Architecture

Description

Unlock the Power of Apache Cassandra: Hands-On Training for Optimal Data Engineering Performance

What You'll Learn?

Overview of NoSQL databases and Cassandra's role.
Understanding the architecture and distributed nature of Cassandra.
Designing effective data models for optimal performance.
Mastering the CQL syntax for creating, updating, and querying data.
Setting up and configuring Cassandra clusters.
Ensuring high availability and fault tolerance.
Strategies for optimizing read and write operations.
Connecting Cassandra with popular data processing frameworks.
Best practices for leveraging Cassandra in production environments.

Who is this for?

IT beginners

Students and Enthusiasts

Data Science beginners

System Architects

Data Architects

Software Developers

Database Administrators

Data Engineers

What You Need to Know?

Familiarity with fundamental concepts of databases, including tables, queries, and basic data modeling principles.

A basic understanding of NoSQL database concepts can be beneficial but is not mandatory.

Proficiency in a programming language, such as Java, Python, or C++, is recommended. Knowledge of data types, variables, and basic programming constructs will be helpful.

Comfort with using the command line interface and basic Linux commands, as Apache Cassandra is often managed through the command line.

A grasp of distributed system concepts will aid in comprehending the architecture and functioning of Apache Cassandra.

An understanding of data engineering principles, data pipelines, and data processing can enhance the appreciation of how Apache Cassandra fits into the broader data ecosystem.

Students should have the ability to set up a development environment, including installing and configuring software on their machines.

More details

Description
Elevate your expertise in data engineering with our comprehensive "Mastering Apache Cassandra: Essential Skills for Data Engineers" course. Designed for both beginners and experienced professionals, this hands-on training program delves deep into the intricacies of Apache Cassandra, a leading NoSQL database, equipping you with essential skills for managing and processing large-scale distributed data.
Key Learning Objectives:
Foundational Understanding: Gain a solid grasp of Apache Cassandra's architecture, distributed nature, and its pivotal role in modern data ecosystems.
Effective Data Modeling: Master the art of designing data models that optimize performance, considering denormalization strategies and schema design trade-offs.
Cassandra Query Language (CQL) Proficiency: Acquire expertise in CQL syntax for seamless data manipulation, covering basic operations, advanced features, and optimization techniques.
Cluster Configuration and Deployment: Learn to set up and configure Cassandra clusters with best practices for deployment, scaling, and ensuring high availability.
Performance Tuning and Optimization: Identify and resolve performance bottlenecks, implementing strategies to optimize both read and write operations.
Scaling and High Availability Strategies: Explore horizontal scaling techniques, add nodes to clusters, and implement robust strategies for high availability and fault tolerance.
Data Consistency and Replication: Understand consistency levels and configure data replication to ensure durability and reliability in distributed environments.
Monitoring and Troubleshooting: Implement effective monitoring solutions and develop troubleshooting skills to address common challenges in Cassandra deployment.
Integration with Data Processing Frameworks: Connect Cassandra seamlessly with popular data processing frameworks, and integrate it into existing data pipelines for comprehensive data solutions.
Real-world Use Cases and Best Practices: Apply your knowledge to real-world scenarios and explore best practices for deploying and leveraging Apache Cassandra in production environments.
Don't miss this opportunity to unlock the full potential of Apache Cassandra and propel your career in data engineering. Enroll now and embark on a journey towards mastering the essential skills needed for success in the dynamic world of distributed data management.
Who this course is for:
IT beginners
Students and Enthusiasts
Data Science beginners
System Architects
Data Architects
Software Developers
Database Administrators
Data Engineers

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