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Struttura del corso
Introduction to BigQuery
- BigQuery architecture and features
- Cost model and pricing structure
- Overview of query execution and storage
Optimizing Queries and Reducing Costs
- Query tuning techniques
- Partitioned and clustered tables
- Monitoring and analyzing query performance
- Hands-on lab: optimizing queries for cost efficiency
Data Ingestion and Transformation
- Loading data from external sources
- Using Dataflow and Dataprep for ETL
- Materialized views and scheduled queries
- Hands-on lab: building a reporting pipeline
Introduction to BigQuery ML
- Overview of machine learning in BigQuery
- Supported model types (linear regression, logistic regression, clustering, etc.)
- SQL syntax for ML models
- Hands-on lab: creating and training a model
Building Predictive Models with BigQuery ML
- Training and evaluating models
- Using ML.EVALUATE and ML.PREDICT
- Integrating predictions into reports
- Hands-on lab: predictive analytics workflow
Best Practices for Enterprise Analytics
- Governance and access control
- Managing large datasets at scale
- Cost control strategies
- Case studies of successful implementations
Summary and Next Steps
Requisiti
- Basic knowledge of SQL
- Familiarity with data management concepts
- Experience with reporting or analytics tools
Audience
- Data analysts
- BI developers
- Data engineers
14 ore
Recensioni (2)
È stato un corso di formazione davvero ottimo, ben preparato e spiegato dal formatore che ha una grande esperienza pratica su GCP.
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