Every (Big) Data Architecture Is The Same

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