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Autor Tópico: Every (Big) Data Architecture Is The Same  (Lida 72 vezes)

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Every (Big) Data Architecture Is The Same
« em: 16 de Novembro de 2022, 10:22 »


Published 11/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 667.91 MB | Duration: 3h 48m

One data architecture blueprint to rule them all.

What you'll learn
How data architectures can be set up in a generic and repetitive way
Be able to identify common components that are present in every data architecture
Work out a blueprint for a data architecture for any project that you are working on, currently, or in the future
Defend design decisions and make conscious choices based on best practices and proven tracks
Learn the place and function of a data mesh and how to best apply it
Requirements
Basic understanding of big data and data science terminology
Rudimentary knowledge of major tools in big data science
My course "The definitive intro to big data science"
Description
This is the only data architecture course on Udemy!In this course we will venture together to work out a data architecture blueprint. This blueprint will exhaustively contain all the components you will ever see and need in any data archtitecture and - perhaps even more importantly so - how to link those components together.We'll talk extensively about every component part of the blueprint and how they interact with one another in a top-down fashion so that we always keep the full picture in mind. We'll learn how data mesh fits in and that we can realize a data mesh setup without any additonal requirements using our data architecture blueprint.Obviously the proof is in the pudding, so we will look at vastly different use cases to see how the data architecture blueprint can be applied to real-life scenarios where business settings are always different but the same key components always play their role.In this course you will learn:- How to set up any data architecture- Learn of a blueprint that you can add to your toolbox as a key ingredient to design data architectures- What a data mesh is and when (not) to use it- Translate the data architecure blueprint to real-life use cases to make it work in any setting- Where to move on from hereon out once you've gotten to know the data architecture blueprintNext to know what this course does tell you, it is also important to realize what it does not tell you. In this course we will not talk extensively about all sorts of tools and frameworks that exist that can do one thing or another. This is not a Spark/Hadoop/NoSQL tutorial. If you are interested in learning what tools work well in which scenarios, please follow my other courses.
Overview
Section 1: Introduction
Lecture 1 Introduction, course goals and audience
Section 2: Every single data architecture ever
Lecture 2 The data architecture blueprint
Lecture 3 The ingestion layer
Lecture 4 On-the-fly enrichments and raw storage
Lecture 5 Micro services and integrated storage
Lecture 6 Integrated ETL and storage
Lecture 7 Case-specific ETL and storage
Lecture 8 The serving layer
Lecture 9 Power-user (data scientist) layer
Lecture 10 How does data mesh fit in?
Lecture 11 Wrap-up
Section 3: Use cases
Lecture 12 Log monitoring
Lecture 13 IoT sensor data
Lecture 14 Media and behavioral tracking
Lecture 15 HR tech and recruitment
Lecture 16 Extra: an abstraction of the blueprint to fit any use case
Lecture 17 Wrap-up
Data professionals who want to advance their career into architectural decision making,Enterprise or software architects that want to add data architecture understanding to their portfolio,Anyone interested in data mesh or data architecture


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