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Engineering Data Mesh in Azure Cloud. Implement data mesh using Microsoft Azure's Cloud Adoption Framework

Engineering Data Mesh in Azure Cloud. Implement data mesh using Microsoft Azure's Cloud Adoption Framework

Aniruddha Deswandikar

Ebook
Decentralizing data and centralizing governance are practical, scalable, and modern approaches to data analytics. However, implementing a data mesh can feel like changing the engine of a moving car. Most organizations struggle to start and get caught up in the concept of data domains, spending months trying to organize domains. This is where Engineering Data Mesh in Azure Cloud can help.
The book starts by assessing your existing framework before helping you architect a practical design. As you progress, you’ll focus on the Microsoft Cloud Adoption Framework for Azure and the cloud-scale analytics framework, which will help you quickly set up a landing zone for your data mesh in the cloud.
The book also resolves common challenges related to the adoption and implementation of a data mesh faced by real customers. It touches on the concepts of data contracts and helps you build practical data contracts that work for your organization. The last part of the book covers some common architecture patterns used for modern analytics frameworks such as artificial intelligence (AI).
By the end of this book, you’ll be able to transform existing analytics frameworks into a streamlined data mesh using Microsoft Azure, thereby navigating challenges and implementing advanced architecture patterns for modern analytics workloads.
  • 1. Introducing Data Meshes
  • 2. Building a Data Mesh Strategy
  • 3. Deploying a Data Mesh Using the Azure Cloud-Scale Analytics Framework
  • 4. Building a Data Mesh Governance Framework Using Microsoft Azure Services
  • 5. Security Architecture for Data Meshes
  • 6. Automating Deployment through Azure Resource Manager and Azure DevOps
  • 7. Building a Self-Service Portal for Common Data Mesh Operations
  • 8. How to Design, Build, and Manage Data Contracts
  • 9. Data Quality Management
  • 10. Master Data Management
  • 11. Monitoring and Data Observability
  • 12. Monitoring Data Mesh Costs and Building a Cross-Charging Model
  • 13. Understanding Data-Sharing Topologies in a Data Mesh
  • 14. Advanced Analytics Using Azure Machine Learning, Databricks, and the Lakehouse Architecture
  • 15. Big Data Analytics Using Azure Synapse Analytics
  • 16. Event-Driven Analytics Using Azure Event Hubs, Azure Stream Analytics, and Azure Machine Learning
  • 17. AI Using Azure Cognitive Services and Azure OpenAI
  • Tytuł: Engineering Data Mesh in Azure Cloud. Implement data mesh using Microsoft Azure's Cloud Adoption Framework
  • Autor: Aniruddha Deswandikar
  • Tytuł oryginału: Engineering Data Mesh in Azure Cloud. Implement data mesh using Microsoft Azure's Cloud Adoption Framework
  • ISBN: 9781805128946, 9781805128946
  • Data wydania: 2024-03-29
  • Format: Ebook
  • Identyfikator pozycji: e_3uiu
  • Wydawca: Packt Publishing