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In this course, you learn about the internals of BigQuery and best practices for designing, optimizing, and administering your data warehouse. Through a combination of lectures, demos, and labs, you learn about BigQuery architecture and how to design optimal storage and schemas for data ingestion and changes. Next, you learn techniques to improve read performance, optimize queries, manage workloads, and use logging and monitoring tools. You also learn about the different pricing models. Finally, you learn various methods to secure data, automate workloads, and build machine learning models with BigQuery ML.
11 modules · 11 labs · 15 total classroom activities
Data analysts, data scientists, data engineers, and developers who perform work on a scale that requires advanced BigQuery internals knowledge to optimize performance.
Big Data and Machine Learning Fundamentals
Introduction to BigQuery, basic data warehousing concepts, distributed data processing concepts, SQL: these are all prerequisites/assumed prior knowledge.
Administrative tasks, data warehouse migrations, analyzing data with BigQuery: these are not the focus of this course and are covered in other courses.
Labs and demos
Appsbroker Academy is an Authorised Training Partner for Google Cloud. Drawing on our own highly skilled engineers’ unique experiences and expertise, we provide dedicated, industry-specific training using real-life examples to help your people to thrive.