Building Data Lakes in Azure

Overview

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.

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

Subjects

Conference Talks