Part 2: Build Solutions with GCP Components

This part will talk about leveraging GCP products to support storage systems, pipelines, and infrastructure in a production environment. It will also cover common operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. By the end of this part, you will have acquired practical knowledge to build efficient Extract, Transform, and Load (ETL) data pipelines over GCP.

This part has the following chapters:

• Chapter 3, Building a Data Warehouse in BigQuery
• Chapter 4, Building Workflows for Batch Data Loading Using Cloud Composer
• Chapter 5, Building a Data Lake Using Dataproc
• Chapter 6, Processing Streaming Data with Pub/Sub and Dataflow
• Chapter 7, Visualizing Data to Make Data-Driven Decisions with Looker Studio
• Chapter 8, Building Machine Learning Solutions on GCP