Azure Data Engineer Associate (DP-203) Cert Prep: 1 Design and Implement Data Storage

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Noah Gift

55:13

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01 - Introduction

01 - Design and implement data storage on Microsoft Azure.mp4

00:39

02 - Quick prerequisite technology overview.mp4

03:42

02 - 1. Design a Data Storage Structure

01 - Design an Azure Data Lake solution.mp4

01:43

02 - Recommend file types for storage.mp4

01:37

03 - Recommend file types for analytical queries.mp4

02:01

04 - Design for efficient querying.mp4

02:00

05 - Design for data pruning.mp4

01:16

06 - Design a folder structure.mp4

02:28

07 - Design a distribution strategy.mp4

01:54

08 - Design a data archiving solution.mp4

02:08

03 - 2. Design a Partition Strategy

01 - Overview of data partitioning.mp4

02:44

02 - Partition strategy.mp4

04:40

04 - 3. Design the Serving Layer

01 - Design analytical stores.mp4

04:43

02 - Design metastores.mp4

05:48

05 - 4. Implement Physical Data Storage Structures

01 - Implement different table geometries.mp4

04:30

02 - Implement data storage structures.mp4

05:54

06 - 5. Implement Data Architectures

01 - Implement data architectures, structures, and serving.mp4

03:32

07 - Conclusion

01 - Summary and next steps.mp4

03:54

Description

Are you preparing for the Microsoft Azure Data Engineering (DP-203) exam, or just looking for a stronger understanding of how to design and implement data storage? Either way, this course, the first in a series, can help you. Noah Gift, founder of Pragmatic A.I. Labs and a Python Software Foundation Fellow, shows you how to design and implement data storage on Azure. Noah walks you through the full process of designing a data storage structure, from designing an Azure Data Lake solution to designing a data archiving solution. He explains horizontal, vertical, and functional data partitioning strategies and how to choose which strategy will work best for your data. Noah goes over designing both analytical stores and metastores, then dives into implementing table geometries, data storage structures, data architectures, and more.

Note: This course was created by Noah Gift. We are pleased to host this training in our library.

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Microsoft Azure

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Noah Gift

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Author of Practical MLOps, Enterprise MLOps, Developing on AWS with C#, Pragmatic AI, and Python for DevOps. Certified on Multiple MLOps certifications including Google-Professional Machine Learning Engineer and AWS Certified Machine Learning - Specialty. Adjunct Professor at Duke MIDS & Northwestern Graduate Data Science & AI. Held business roles including CTO, general manager, consulting CTO, and cloud architect. Consults with start-ups and other companies on machine learning and cloud architecture. AWS ML Hero, Python Software Foundation Fellow, AWS Subject Matter on Machine Learning, AWS Certified Solutions Architect, AWS Certified Machine Learning Specialist, AWS Certified Big Data Specialist, Google Certified Professional Architect, and AWS Academy Accredited Instructor. Published books, videos, and courses on cloud machine learning, DevOps, Python, Data Science, Big Data and AI. ★ Specialties ★ ° Cloud-native Machine Learning and AI ° Directly teaching cutting edge skills to students that lead to jobs ° Creating world-class content in all forms ° Building Companies ° Shipping new Products ° Leading and growing engineering teams ° Production Machine Learning, Deep Learning, Big Data, and AI ° Serverless Data Engineering ° Advising Early Stage Startups/Consulting CTO services ° Distributed Systems and Scalability

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