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מתחיל 4 June 2026 15:22

נגמר 4 June 2026

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Building Data Lakes in Azure

Learn to build and leverage data lakes in Azure using Databricks and Synapse Analytics. Explore key services, implementation strategies, and querying techniques for modern data environments.
PASS Data Community Summit via YouTube

PASS Data Community Summit

6076 קורסים


1 hour 6 minutes

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התקדמות בקצב שלך

Conference Talk

שדרוג אופציונלי זמין

סקירה כללית

Learn to build and leverage data lakes in Azure using Databricks and Synapse Analytics. Explore key services, implementation strategies, and querying techniques for modern data environments.

סילבוס

  • Introduction to Data Lakes
  • Definition and Benefits of Data Lakes
    Overview of Azure Data Lake Architecture
    Key Components and Tools in Azure
  • Azure Data Lake Services
  • Introduction to Azure Data Lake Storage (ADLS)
    Azure Databricks Overview
    Azure Synapse Analytics Introduction
  • Setting Up a Data Lake in Azure
  • Creating and Configuring Azure Data Lake Storage
    Setting Up Azure Databricks and Synapse Analytics Workspaces
    Managing Access and Security in Azure Data Lakes
  • Data Ingestion and Transformation
  • Ingesting Data into the Data Lake
    Using Azure Data Factory for ETL Processes
    Transforming Data with Azure Databricks
  • Data Management and Storage Optimization
  • Organizing Data in Azure Data Lake Storage
    Implementing File Systems and Hierarchies
    Data Governance and Compliance
  • Querying and Analyzing Data
  • Querying with Azure Synapse Analytics
    Using Databricks for Data Analysis and ML
    Integration with Power BI for Visualization
  • Implementation Strategies
  • Best Practices for Data Lake Design and Architecture
    Data Lake Lifecycle Management
    Real-world Use Cases and Scenarios
  • Performance Tuning and Optimization
  • Optimizing Data Lake Performance
    Cost Management and Scale Considerations
    Monitoring and Analytics Tools
  • Project: Building a Data Lake in Azure
  • Defining Project Scope and Requirements
    Implementing End-to-End Data Lake Solution
    Final Presentation and Review
  • Conclusion and Next Steps
  • Summary of Key Learnings
    Future Trends in Data Lake Technologies
    Additional Resources and Learning Paths

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