Building Scalable Data Services Architecture with Azure

Course Summary

This course provides participants with the essentials for designing, implementing, and managing secure, scalable data architectures with Microsoft Azure. Azure’s data services, integration pipelines, governance, and performance optimization, are covered with a focus on real-world applications. Gain hands-on experience building cost-effective solutions and integrating AI-driven analytics into data workflows.

Prerequisites:

  • Familiarity with Azure services and basic clouod computing
  • Basic understanding of relational and non-relational databases
  • Experience with programming or scripting
Purpose
Learn the esentials of scalable data architectures with Microsoft Azure
Audience
IT professionals seeking practical expertise in Azure's data ecosystem
Role
Data Architects | Data Engineers | Software Developers
Skill level
Intermediate
Style
Lecture | Hands-on Activities | Labs
Duration
3 days
Related technologies
SQL | Python | AI | Machine Learning

 

Course objectives
  • Design data architectures using Azure services
  • Implement and manage relational and non-relational databases on Azure
  • Build end-to-end data integration pipelines using Azure Data Factory
  • Apply analytics tools to gain insights from structured and unstructured data
  • Establish data security and governance standards to comply with regulatory requirements
  • Optimize the performance and scalability of Azure-based data solutions
  • Integrate AI and machine learning capabilities into data workflows to derive actionable insights
  • Effectively manage costs while delivering robust data solution

What you'll learn:

In this Building Scalable Data Services Architecture with Azure course, you'll learn:

Introduction to Azure Data Services

  • Overview of Azure's data-related offerings, such as Azure SQL Database, Azure Cosmos DB, Azure Data Lake, Azure Synapse Analytics, and more
  • Understanding the role of data architecture in modern cloud environments

Data Storage Options

  • Relational vs. non-relational databases
  • Implementing Azure SQL Database and Azure Cosmos DB for structured and unstructured data

Data Integration and ETL (Extract, Transform, Load)

  • Using Azure Data Factory to orchestrate and automate data workflows
  • Creating pipelines for data movement across various sources

    Big Data and Analytics

    • Leveraging Azure Synapse Analytics for large-scale data processing
    • Implementing real-time analytics with Azure Stream Analytics

    Data Governance and Security

    • Best practices for securing data in Azure
    • Role-based access control, encryption, and compliance features
    • Introduction to Purview for data governance

    Scalability and Performance Optimization

    • Strategies for scaling databases and storage
    • Performance tuning and monitoring tools, such as Azure Monitor and Query Performance Insights

    AI and Machine Learning Integration

    • Exploring how Azure Machine Learning can be integrated with data services for predictive analytics
    • Enabling AI-driven insights from datasets stored in Azure

    Cost Management and Optimization

    • Understanding Azure's pricing models for data services
    • Techniques for optimizing costs without sacrificing performance

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