Level: Intermediate to Advanced
Prerequisite: See Below
The North American market is dominated by three hyperscale public cloud service providers: Google Cloud, Amazon AWS, and MS Azure. Each CSP provides several powerful options for building data warehouse solutions.
In this day-long course, students will gain hands-on experience in the steps needed to build a data warehouse on Google Cloud. The focus will be on Google BigQuery as the data platform and on other Google-native tools for working with data. Students will learn by doing: how to load data into BigQuery, how to choose a data model most suitable to the project goals, and how to use the data warehouse for reporting and machine learning.
Data will be loaded into BigQuery using both batch and streaming approaches. Data will be transformed in an ETL pipeline using Google Cloud Dataflow. Looker Studio will be used to create reports and dashboards. In-database machine learning will be demonstrated using BigQuery ML.
All of the hands-on work will be with Google Cloud tools, but alternative options available within the Google Marketplace will also be discussed.
You Will Learn
- The main features of Google BigQuery, and its strengths and weaknesses as a cloud data platform
- How to choose a BQ data model that works for your project
- How to load data into BigQuery, using both batch and streaming interfaces
- How to create reports and dashboards with Looker Studio
- How to create and train machine learning models within BigQuery
- How to create a Google Cloud account and project that can be used after the course is complete
- Data warehouse architects and developers
- Business intelligence developers
- Cloud solution architects
Familiarity with data warehousing, business intelligence, and cloud computing concepts will be helpful.
Some experience with SQL will be helpful.
No prior knowledge of Google Cloud is required.
Each student must bring a laptop computer with any operating system. A web browser is required (Chrome is recommended.) A dual-core CPU (eg Intel Core I5 or better) with 8GB of RAM is recommended.
Laptop setup is required BEFORE the conference. Instructions will be emailed to registrants prior to the event.
There is no time allotted in class for laptop preparation.
* Enrollment is limited to 40 attendees.