Data Architecture for Data Engineers: Practical Approaches

سرفصل های دوره

Building Scalable, Efficient Data Solutions with Real-World Applications

1 - Introduction to the Instructor and Course Overview

1 - Meet Your Instructor

2 - Course Structure and Objectives

2 - Introduction to Data Architecture

3 - Key Tenets in Data Architecture and Governance

4 - Overview of Data Architecture

5 - Types of Data Architectures

6 - Monolithic Architecture

7 - Distributed Architecture

8 - Cloudbased Architecture Use Cases

9 - Choosing the Optimal Data Architecture

10 - Additional Readings.html

3 - Data Modeling for Effective Architectures

11 - Introduction to Data Modeling

12 - Database Types

13 - Database Design Approaches

14 - Normalization

15 - Denormalization

16 - Normalization Denormalization How to choose

17 - Case Study

18 - Additional Readings.html

4 - Architecting Data Pipelines

19 - Introduction to Data Pipelines

20 - ETL vs ELT Processes

21 - Data Pipeline Tools Best Practices

22 - Batch Data Processing

23 - Realtime Data Processing

24 - Batch vs Realtime Data Processing

25 - Architecting Robust Pipelines I

26 - Architecting Robust Pipelines II

27 - Case Study

28 - Additional Readings.html

5 - Modern Data Architectures

29 - Data Lakes and Data Warehouses

30 - Data Lakehouse Architecture

31 - Data Mesh and Data Fabrics

32 - Case Study

33 - Additional Readings.html

6 - Cloud Data Architecture Tools and Technologies

34 - AWS for Data Engineers

35 - Azure for Data Engineers

36 - Hybrid and Multicloud Architectures

37 - Additional Readings.html

7 - Cheat Sheet and Course WrapUp

38 - StepbyStep Guide to Choosing an Architecture

39 - Road to Becoming a Data Architect

40 - Other Courses by Manas Jain.html

41 - Feedback Course Conclusion

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تولید کننده: Udemy