Building Data Lakes in Azure

Overview

Syllabus

• 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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Subjects

Conference Talks