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Duration 14 hours (2 days)
Course Outline
Introduction to BigQuery
- BigQuery architecture and key features
- Cost model and pricing structure
- Overview of query execution and storage mechanisms
Query Optimization and Cost Reduction
- Advanced query tuning techniques
- Implementation of partitioned and clustered tables
- Monitoring and analyzing query performance
- Hands-on lab: optimizing queries for cost efficiency
Data Ingestion and Transformation
- Loading data from various external sources
- Utilizing Dataflow and Dataprep for ETL processes
- Configuring materialized views and scheduled queries
- Hands-on lab: building a robust reporting pipeline
Introduction to BigQuery ML
- Overview of machine learning capabilities within BigQuery
- Supported model types (linear regression, logistic regression, clustering, etc.)
- SQL syntax specific to ML models
- Hands-on lab: creating and training a model
Building Predictive Models with BigQuery ML
- Training and evaluating model performance
- Utilizing ML.EVALUATE and ML.PREDICT functions
- Integrating predictions into reporting dashboards
- Hands-on lab: executing a predictive analytics workflow
Best Practices for Enterprise Analytics
- Governance and access control strategies
- Managing large-scale datasets effectively
- Strategies for cost control
- Case studies of successful enterprise implementations
Summary and Next Steps
Requirements
- Foundational knowledge of SQL
- Familiarity with core data management concepts
- Experience working with reporting or analytics tools
Target Audience
- Data analysts
- BI developers
- Data engineers
Testimonials (2)
The final day which is the Machine Learning Topic
John Erick Baltazar - Globe Telecom
Course - Google BigQuery
It was a really good training course, well prepared and explained by the trainer with great hands on experience on GCP.
