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Azure Data Services and Data Management Training

About the Training

The Azure Data Services and Data Management Training is a significant opportunity. This training focuses on cloud-based data management techniques. Participants will learn about the wide range of Azure’s data services and how to effectively use them. This knowledge facilitates data storage, processing, and analysis.

The training covers services such as Azure SQL Database and Azure Cosmos DB. Participants will learn how to manage these database solutions, enabling them to develop high-performance and scalable applications. This also ensures data security and compliance, which increases the confidence of businesses.

Topics like Azure Data Lake and Azure Data Factory are also addressed. Participants will learn techniques for large-scale data storage and integration, making it easier to manage complex data workflows. Additionally, these techniques accelerate data-driven decision-making processes, enhancing the efficiency of business operations.

The training includes data analysis and reporting tools as well. Participants will explore Azure Analysis Services and Power BI, which transform data into meaningful and impactful visuals. These tools also simplify the creation of business intelligence reports, contributing to strategic planning for businesses.

The Azure Data Services and Data Management Training equips participants with practical skills that help them develop effective data management projects on the Azure platform. The training fosters expertise in data management and cloud services, allowing participants to successfully plan and implement data management strategies.

In conclusion, this training opens the door to the world of Azure Data Services and data management. Participants will gain in-depth knowledge of cloud-based data management, enabling them to succeed in data-centric projects. By the end of the training, participants will be able to effectively manage data management and analysis projects, significantly contributing to their professional development.

What Will You Learn?

  • Fundamentals of Azure Data Services: Azure’s data services and components.
  • Database Management: Azure SQL Database, Azure Cosmos DB.
  • Data Storage and Processing: Azure Data Lake, Azure Synapse Analytics.
  • Data Security and Protection: Encryption, access control, backup strategies.
  • Disaster Recovery: High availability and disaster recovery solutions.
  • Data Integration: Data transfer and ETL processes.
  • Performance Optimization: Monitoring and improving database performance.
  • Case Studies and Practical Scenarios: Hands-on experience through real-world examples.

Prerequisites

  • Familiarity with basic cloud computing and database concepts.
  • Knowledge of SQL and basic database management.
  • A general introduction to the Azure platform is preferred but not required.

Who Should Attend?

  • Database Administrators and Developers.
  • Cloud Computing Specialists.
  • IT and Data Management Professionals.
  • Anyone interested in data management and analysis on Azure

Outline

Introduction: Overview of Azure Data Services
  • Azure’s data services and architecture
  • Advantages of cloud-based data management
Database Management
  • Working with Azure SQL Database and Azure Cosmos DB
  • Creating, configuring, and managing databases
Data Storage and Processing
  • Using Azure Data Lake and Azure Synapse Analytics
  • Techniques for large-scale data storage and processing
Data Security and Protection
  • Data encryption, access control, and authentication methods
  • Data backup and restoration strategies
Disaster Recovery
  • High availability and disaster recovery solutions
  • Disaster recovery planning and implementation
Data Integration and ETL
  • Data transfer methods and tools
  • ETL processes and automation
Performance Optimization
  • Techniques for monitoring and improving database performance
  • Identifying and resolving performance bottlenecks
Practical Scenarios and Case Studies
  • Hands-on exercises based on real-world examples
  • Problem-solving and best practices

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