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


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