Transforming data | PySpark, T-SQL & Dataflows in Microsoft Fabric | DP-600 EXAM PREP (7 of 12)

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In this video (7 of 12 in the series), cover the following:
Data cleansing:
Implement a data cleansing process
Identify and resolve duplicate data, missing data, or null values
Convert data types by using Dataflows or PySpark
Filter data

Data enrichment
Merge or join data
Enrich data by adding new columns or tables

Data modelling
Implement a star schema for a lakehouse or warehouse, including Type 1 and Type 2 slowly changing dimensions
Implement bridge tables for a lakehouse or a warehouse
Denormalize data
Aggregate or de-aggregate data

This video is part of the DP-600 Exam Preparation series:    • DP-600 Exam Preparation  

Timeline
0:00 Intro
1:29 Data cleansing process
2:26 Introduction to the dataset
3:31 Dataflow: data cleaning
6:55 T-SQL: data cleaning
10:51 PySpark: data cleaning
20:25 Star schema
22:41 Slowly-changing dimensions
23:36 Type 1 SCD
24:27 Type 2 SCD
27:53 Bridge tables
28:56 Implementing a bridge table in T-SQL
32:53 Normalized vs Denormalized data
34:53 Data aggregation (and de-aggregation)
37:54 Practice Questions
43:45 Outro and next steps

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