The Ultimate Guide to Designing and Customizing Scalable Big Data Architecture

What you'll learn
Understand Big Data for beginners
Master Big Data Architecture layers from data ingestion to data analytics
Learn advanced Big data layers as Data Security and Data Monitoring
Design of a complete Real World Big Data Architecture
Understand Big Data Architecture layers

Requirements
No requirement , for Big Data Beginners
No programming or Big Data experience needed. You will learn everything you need to know

Description
The "Big Data Architectures" course provides an introduction to Big Data and its significance in today's data-driven world. The course covers the five V's of Big Data, namely volume, velocity, variety, veracity, and value, and offers a comprehensive overview of Big Data architectures.Students will learn about the different layers that make up a Big Data architecture, including the data source layer, data ingestion layer, data storage layer, distributed processing layer, data query layer, data workflow management and scheduling, and data visualization layer. The course also covers advanced topics such as data security, monitoring, and system management.The importance of customizing Big Data architectures and best practices for doing so are discussed, along with popular Big Data analytics tools and frameworks. To help students apply their knowledge in a practical setting, the course includes a hands-on project that allows them to design a complete Big Data architecture for a social media analytics platform.Whether you're a beginner seeking to expand your knowledge of Big Data or an experienced data professional looking to develop expertise in Big Data architectures, "Big Data Architectures" is the ultimate guide for mastering the complex world of Big Data. With this course, students will gain the skills and knowledge necessary to design, implement, and manage Big Data architectures effectively.

Overview
Section 1: Inroduction

Lecture 1 Introduction to Big Data Architectures Course

Lecture 2 Agenda

Section 2: Introduction to Big Data

Lecture 3 Introduction to Big Data

Section 3: Exploring Big Data Architectures

Lecture 4 Exploring Big Data Architectures: A Comparison of Kappa, Lambda, and Microservic

Section 4: Data Ingestion

Lecture 5 Data Source and Data Ingestion layers

Section 5: Big Data Storage

Lecture 6 Big Data Storage Layer

Section 6: Big Data Distributed Processing

Lecture 7 Big Data Processing Layer

Lecture 8 Big Data Processing Tools : Apache Hadoop Mapreduce, Spark, Flink and Storm

Section 7: Big Data Querying

Lecture 9 Big Data Querying Layer | Apache Hive, PiG

Section 8: Big Data Workflow Management and Scheduling

Lecture 10 Big Data Workflow Management and Scheduling | Apache Airflow

Section 9: Data Visualisation

Lecture 11 Big Data Visualisation

Section 10: Advanced Big Data Architecture Layers

Lecture 12 Advanced QOS Big Data Architecture layers

Section 11: Customizing Scalable Big Data Architecture

Lecture 13 Customizing Scalable Big Data Architecture

Section 12: Designing Real World Big Data Architecture

Lecture 14 Hands-on Big Data Architecture : Design a real world Big Data Architecture

Beginner Big Data students and engineers,Beginner in Data Analytics and Data Engineering,Anyone seeking to develop expertise in Big Data architectures,Beginner-level and professionals,Experienced data professionals seeking to expand their knowledge,Big Data analysts and engineers,Everyone who want to master big Data Architecture

https://www.udemy.com/course/big-data-architecture-course/