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Welcome to our Big Data Architecture course playlist, where we will explore the fascinating world of Big Data and its architectural layers. In this playlist you'll find a series of videos covering everything from the basics of Big Data to advanced topics like data management, security, and scalability.

we dive into the architectural layers of Big Data, including data storage, processing and analysis, and explore the different IT tools and technologies commonly used in each layer.
we cover important topics such as data lakes, data warehousing and data visualization, and provide

You will learn about popular Big Data tools such as Hadoop, Spark, Flink, Kafka, Airflow, Kibana, Elasticsearch, Hbase, Hive, Pig, Mapreduce, Storm and NoSQL databases, and how to select the right tools for your specific business requirements. We also cover the different types of Big Data architecture, including batch processing, stream processing, and real-time processing, and how to design a system that can process large amounts of data with high speed and variability.
By the end of this playlist, you will have a good understanding of Big Data Architecture and its different layers and IT tools. You will gain the knowledge and skills necessary to design and implement a complete Big Data system that meets the needs of your organization.

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Big Data can come from a wide variety of sources, such as social media, mobile devices, sensors and other Internet of Things (IoT) devices. To understand this data and gain insights from it, we need specialized tools and techniques. That's where Big Data architectures come into the picture.

A Big Data architecture is a structure or framework designed to process large and complex data sets efficiently and effectively. A well-designed Big Data architecture can help organizations process, store and analyze large data sets in a way that is both scalable and cost-effective.
The agenda of the course:

Module 1: Overview of Big Data Architecture
Introduction to Big Data Architectures.
Kappa vs Lambda vs Microservices Big Data Architecture.
Module2: Big Data Architecture Layers
Data source layer
Data recording layer
Data storage layer
Distributed processing layer: batch and real-time processing
Data query
Data workflow management and planning
Data visualization layer
Module 3: Advanced QOS Big Data Layers
Data security layer, data monitoring, system management
Module 4: Customizing Big Data Architectures
The importance of adapting Big Data architectures
Best practices for adapting big data architectures
Hands-on project
Design a complete Big Data architecture of the Social Media Analytics Platform

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