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Implement a data engineering solution with Azure Databricks

    Seminarinhalt

    Erfahren Sie, wie Sie die Leistungsfähigkeit von Apache Spark und leistungsstarke Cluster auf Basis der Azure Databricks-Plattform nutzen können, um große Data-Engineering-Workloads in der Cloud zu bewältigen.

    Programm

    Perform incremental processing with spark structured streaming
    • Set up real-time data sources for incremental processing
    • Optimize Delta Lake for incremental processing in Azure Databricks
    • Handle late data and out-of-order events in incremental processing
    • Monitoring and performance tuning strategies for incremental processing in Azure Databricks
    Implement streaming architecture patterns with Delta Live Tables
    • Event driven architectures with Delta Live tables
    • Ingest data with structured streaming
    • Maintain data consistency and reliability with structured streaming
    • Scale streaming workloads with Delta Live tables
    Optimize performance with Spark and Delta Live Tables
    • Optimize performance with Spark and Delta Live Tables
    • Perform cost-based optimization and query tuning
    • Use change data capture (CDC)
    • Use enhanced autoscaling
    • Implement observability and data quality metrics
    Implement CI/CD workflows in Azure Databricks
    • Implement version control and Git integration
    • Perform unit testing and integration testing
    • Manage and configure your environment
    • Implement rollback and roll-forward strategies
    Automate workloads with Azure Databricks Jobs
    • Implement job scheduling and automation
    • Optimize workflows with parameters
    • Handle dependency management
    • Implement error handling and retry mechanisms
    • Explore best practices and guidelines
    Manage data privacy and governance with Azure Databricks
    • Implement data encryption techniques in Azure Databricks
    • Manage access controls in Azure Databricks
    • Implement data masking and anonymization in Azure Databricks
    • Use compliance frameworks and secure data sharing in Azure Databricks
    • Use data lineage and metadata management
    • Implement governance automation in Azure Databricks
    Use SQL Warehouses in Azure Databricks
    • Get started with SQL Warehouses
    • Create databases and tables
    • Create queries and dashboards
    Run Azure Databricks Notebooks with Azure Data Factory
    • Understand Azure Databricks notebooks and pipelines
    • Create a linked service for Azure Databricks
    • Use a Notebook activity in a pipeline
    • Use parameters in a notebook

    Zielgruppen

    • Data Engineer
    • Developer
    • Data Scientist
    • Data Analyst

    Vorkenntnisse

    keine

    Downloads

      1 Tag ab € 690,-
      Termin anfragen
      Trainings-ID:
      DP-3027

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