Data Warehousing on Google Cloud Platform

1h 17mIntermediate2024-08-27

Authors

Nikiya Simpson

MBA, Developer, Expert in Data-Driven Web Applications

Course details

Join instructor Nikiya Simpson as she guides you through the fundamentals and advanced concepts of data management in Google Cloud. Get an introduction to cloud data storage principles including object storage and relational and nonrelational databases. Learn about Google Cloud's diverse data storage offerings such as Cloud Storage, Cloud SQL, Spanner, Bigtable, Firestore, Memorystore, and more. Along the way, Nikiya shows you how to organize datasets, manage BigQuery tables, and run efficient SQL queries, before turning to more advanced topics like optimizing data warehouses, query performance, data loading techniques, and leveraging BigQuery ML for predictive analytics. Whether you're a data analyst, a data scientist, a developer, or simply enthusiastic about cloud data management, this course is designed to equip you with the knowledge required to leverage the full power of Google Cloud.

Skills covered

Google Cloud PlatformData EngineeringSoftware Development ToolsGoogleCloud PlatformsCloud ComputingData ScienceSoftware DevelopmentDeep Dive (X:Y)

Concepts

0. Introduction

01 - Data warehousing in Google Cloud Platform
02 - Data warehousing overview

1. Data Storage in Google Cloud

03 - Cloud data storage fundamentals
04 - Google Cloud data storage options
05 - Cloud Storage
06 - Cloud SQL
07 - Spanner
08 - Bigtable and Firestore
09 - Memorystore
10 - BigQuery

2. Organization of BigQuery Data

11 - BigQuery data warehouse solution
12 - BigQuery datasets
13 - BigQuery tables
14 - Demo - BigQuery datasets
15 - Demo - Quick review of BigQuery tables
16 - Demo - Public datasets

3. BigQuery SQL

17 - Overview of BigQuery SQL
18 - Tips on running queries in BigQuery
19 - BigQuery SQL functions
20 - Demo - Create views and saved queries

4. Advanced BigQuery Topics

21 - External data sources in BigQuery
22 - Creating labels in BigQuery
23 - Table partitioning in BigQuery
24 - Data migration
25 - Using Google Cloud Shell for BigQuery
26 - BigQuery API and SDKs

5. BigQuery ML

27 - Introduction to BigQuery ML
28 - Demo - Predictive analytics using SQL and BigQuery

6. Best Practices for Data Warehouses and BigQuery

29 - Data warehouse design considerations
30 - Data load options
31 - Storage considerations for data warehouses
32 - Query optimization
33 - Monitoring and logging

Conclusion

34 - What's the future of data warehousing
35 - How does AI affect data engineering and data science
36 - Conclusion