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Duration 14 hours
Course Outline
BigQuery Foundations
- BigQuery architecture and core capabilities
- Pricing models and cost structures
- Overview of storage and query execution mechanisms
Query Optimization and Cost Management
- Advanced query tuning methods
- Utilizing clustered and partitioned tables
- Tracking and evaluating query performance
- Lab session: Enhancing query efficiency to reduce costs
Data Ingestion and Processing
- Importing data from diverse external sources
- Leveraging Dataflow and Dataprep for ETL processes
- Implementing materialized views and scheduled queries
- Lab session: Constructing a streamlined reporting pipeline
Getting Started with BigQuery ML
- Introduction to machine learning within BigQuery
- Supported model types (including linear regression, logistic regression, and clustering)
- SQL commands for managing ML models
- Lab session: Building and training a basic model
Developing Predictive Models with BigQuery ML
- Techniques for training and model evaluation
- Utilizing ML.EVALUATE and ML.PREDICT functions
- Embedding predictions into reporting outputs
- Lab session: Executing a complete predictive analytics workflow
Enterprise Analytics Best Practices
- Data governance and access management
- Handling large-scale datasets effectively
- Strategies for maintaining cost control
- Review of successful implementation case studies
Recap and Future Directions
Requirements
- Fundamental understanding of SQL
- Basic grasp of data management principles
- Prior experience with analytics or reporting 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.
