Course Outline

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

Requirements

  • Basic knowledge of SQL
  • Familiarity with data management concepts
  • Experience with reporting or analytics tools

Audience

  • Data analysts
  • BI developers
  • Data engineers
 14 Hours

Custom Corporate Training

Training solutions designed exclusively for businesses.

  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

Price per private group, online live training, starting from 3200 € + VAT*

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