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Data Warehousing with Google BigQuery: Storage Design, Query Optimization, and Administration

  • Código del Curso GO9096
  • Duración 3 días

Otros Métodos de Impartición

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Método de Impartición

Este curso está disponible en los siguientes formatos:

  • Cerrado

    Cerrado

  • Clase de calendario

    Aprendizaje tradicional en el aula

  • Aprendizaje Virtual

    Aprendizaje virtual

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In this course, you learn about the internals of BigQuery and best practices for designing, optimizing, and administering your data warehouse. Through a combination of lectures, demos, and labs, you learn about BigQuery architecture and how to design optimal storage and schemas for data ingestion and changes. Next, you learn techniques to improve read performance, optimize queries, manage workloads, and use logging and monitoring tools. You also learn about the different pricing models. Finally, you learn various methods to secure data, automate workloads, and build machine learning models with BigQuery ML.

Company Events

These events can be delivered exclusively for your company at our locations or yours, specifically for your delegates and your needs. The Company Events can be tailored or standard course deliveries.

Calendario

Parte superior

Dirigido a

Parte superior

Data analysts, data scientists, data engineers, and developers who perform work on a scale that requires advanced BigQuery internals knowledge to optimize performance.

Objetivos del Curso

Parte superior
  • Describe BigQuery architecture fundamentals.
  • Implement storage and schema design patterns to improve performance
  • Use DML and schedule data transfers to ingest data.
  • Apply best practices to improve read efficiency and optimize query performance.
  • Manage capacity and automate workloads.
  • Understand patterns versus anti-patterns to optimize queries and improve read performance.
  • Use logging and monitoring tools to understand and optimize usage patterns.
  • Apply security best practices to govern data and resources.
  • Build and deploy several categories of machine learning models with BigQuery ML.
  • BigQuery Architecture Fundamentals
  • Storage and Schema Optimizations
  • Ingesting Data
  • Changing Data
  • Improving Read Performance
  • Optimizing and Troubleshooting Queries
  • Workload Management and Pricing
  • Logging and Monitoring
  • Security in BigQuery
  • Automating Workloads
  • Machine Learning in BigQuery

Pre-requisitos

Parte superior
  • Big Data and Machine Learning Fundamentals
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