The Introduction to Google Cloud for Data Analysts training course is designed for beginner data analysts, SQL developers, and software engineers to start using Google Cloud for insightful, scalable, and responsive data analysis and impactful data visualization.
This course will begin with learning about the BigQuery Serverless data warehouse on Google Cloud and understand the advantages of using columnar vs. row-based data stores for effective structured data analysis. After reviewing key SQL concepts for popular data analysis use cases, students will learn how to import data into BigQuery and how to ensure data quality once it has been imported. Next, students will learn how to improve the performance of the data analysis SQL queries by exploring how optimizations for columnar data stores with table partitions differ from traditional normalization/denormalization techniques in relational databases. Students will also learn about more advanced SQL 2011 standard features such as arrays and structs for semi-structured data analysis. The remainder of the course will cover Data Studio for building effective and actionable dashboards based on the results of your analysis. Students will learn how to create and share BigQuery-based reports and to ensure that the reports are shared safely with role-based access control and row-level access security. The course also delves into working with BigQuery ML for predictive analytics to generate experimental regression and classification models with sample datasets.
This course targets beginner data analysts and SQL developers who have some experience with relational databases like Oracle, SQL Server, MySQL, or PostgreSQL. The course will be conducted on the Google Cloud Platform.
Purpose
|
Learn how to perform insightful and responsive data analysis at scale and delight the consumers of the analysis with effective data visualizations. |
Audience
|
Beginner data analysts and SQL developers who have some experience with relational databases like Oracle, SQL Server, MySQL or PostgreSQL. |
Role
| Business Analyst - Technical Manager |
Skill Level
| Introduction |
Style
| Fast Track - Learning Spikes - Workshops |
Duration
| 2 Days |
Related Technologies
| Google Cloud |
Productivity Objectives
- Describe the capabilities of Google Cloud for structured data analytics
- Adopt basic and advanced SQL capabilities for common data analysis use cases
- Modify SQL statements to improve their performance and reduce associated costs
- Build effective visualization dashboards based on visual theory techniques