Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Introduction to BigQuery
- BigQuery architecture and key features
- Cost models and pricing structures
- Insights into query execution and storage mechanisms
Query Optimization and Cost Reduction
- Techniques for tuning queries
- Implementation of partitioned and clustered tables
- Monitoring and analysis of query performance
- Hands-on lab: optimizing queries for cost efficiency
Data Ingestion and Transformation
- Loading data from external sources
- Utilizing Dataflow and Dataprep for ETL processes
- Employing materialized views and scheduled queries
- Hands-on lab: constructing a reporting pipeline
Overview of BigQuery ML
- Introduction to machine learning capabilities within BigQuery
- Supported model types (linear regression, logistic regression, clustering, etc.)
- SQL syntax for defining ML models
- Hands-on lab: creating and training a model
Developing Predictive Models with BigQuery ML
- Training and model evaluation strategies
- Utilizing ML.EVALUATE and ML.PREDICT functions
- Integrating predictions into business reports
- Hands-on lab: executing a predictive analytics workflow
Best Practices for Enterprise Analytics
- Governance and access control frameworks
- Managing large datasets at scale
- Strategies for cost control
- Case studies of successful enterprise implementations
Summary and Recommended Next Steps
Requirements
- Foundational understanding of SQL
- Familiarity with core data management principles
- Prior experience with reporting or analytics platforms
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.
