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Duration 28 hours
Course Outline
Introduction
- Overview of the Google BigQuery ecosystem.
Getting Started
- Setting up a Google Cloud account.
- Exploring the BigQuery Web UI.
- Creating and managing datasets and tables.
- Methods for loading data into BigQuery.
- Executing basic SQL queries within BigQuery.
SQL Querying in BigQuery
- Advanced SQL querying techniques.
- Data aggregation using GROUP BY clauses.
- Techniques for filtering and sorting data.
- Utilizing date and time functions.
- Joining multiple tables.
- Working with subqueries and window functions.
Advanced BigQuery Features
- Exporting data from BigQuery.
- Implementing user-defined functions (UDFs).
- Managing and scheduling queries.
- Introduction to BigQuery scripting.
- Handling arrays and structured data (structs).
- Processing JSON data.
BigQuery Optimization
- Techniques for optimizing query performance.
- Implementing partitioning and clustering for tables.
- Analyzing the Query Execution Plan.
- Troubleshooting and debugging complex queries.
- Cost control strategies and billing best practices.
- Security management and access control in BigQuery.
Advanced Topics and Integration
- Real-time data analysis using streaming data.
- Integrating BigQuery with Google Data Studio.
- Introduction to BigQuery ML for machine learning tasks.
- Building and deploying machine learning models via BigQuery ML.
- Data lake integration with BigQuery.
Summary and Next Steps
Requirements
- A foundational understanding of databases and SQL concepts.
Target Audience
- Data analysts.
- Database administrators.
Testimonials (2)
The final day which is the Machine Learning Topic
John Erick Baltazar - Globe Telecom
Course - Google BigQuery
The scheduling of every topic and the breaks inserted it helps in digesting the information specially to the newbie to the topic
