ETL Pipelines
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01. Introduction
02. Lesson Overview
03. World Bank Datasets
04. How to Tackle the Exercises
05. Extract
06. Exercise: CSV
07. Exercise: JSON and XML
08. Exercise: SQL Databases
09. Extracting Text Data
10. Exercise: APIs
11. Transform
12. Combining Data
13. Exercise: Combining Data
14. Cleaning Data
15. Exercise: Cleaning Data
16. Exercise: Data Types
17. Exercise: Parsing Dates
18. Matching Encodings
19. Exercise: Matching Encodings
20. Missing Data - Overview
21. Missing Data - Delete
22. Missing Data - Impute
23. Exercise: Imputation
24. SQL, optimization, and ETL - Robert Chang Airbnb
25. Duplicate Data
26. Exercise: Duplicate Data
27. Dummy Variables
28. Exercise: Dummy Variables
29. Outliers - How to Find Them
30. Exercise: Outliers Part 1
31. Outliers - What to do
32. Exercise: Outliers - Part 2
33. AI and Data Engineering - Robert Chang Airbnb
34. Scaling Data
35. Exercise: Scaling Data
36. Feature Engineering
37. Exercise: Feature Engineering
38. Bloopers
39. Load
40. Exercise: Load
41. Putting It All Together
42. Exercise: Putting It All Together
43. Lesson Summary
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39. Load
Load
47 Load V1 V1
Links to Other Data Storage Systems
ranking of database engines
Redis
Cassandra
Hbase
MongoDB
Overview of the Load Part of the Lesson
Load Walk Through
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