Deswandikar Engineering Data Mesh in Azure Cloud

Implement data mesh using Microsoft Azure's Cloud Adoption Framework
1. Auflage 2024
ISBN: 978-1-80512-894-6
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 314 Seiten

No detailed description available for "Engineering Data Mesh in Azure Cloud".

Autoren/Hrsg.

Deswandikar, Aniruddha

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Warehouse

Inhaltsverzeichnis

Table of Contents - Introducing Data Meshes
- Building a Data Mesh Strategy
- Deploying a Data Mesh Using the Azure Cloud-Scale Analytics Framework
- Building a Data Mesh Governance Framework Using Microsoft Azure Services
- Security Architecture for Data Meshes
- Automating Deployment through Azure Resource Manager and Azure DevOps
- Building a Self-Service Portal for Common Data Mesh Operations
- How to Design, Build, and Manage Data Contracts
- Data Quality Management
- Master Data Management
- Monitoring and Data Observability
- Monitoring Data Mesh Costs and Building a Cross-Charging Model
- Understanding Data-Sharing Topologies in a Data Mesh
- Advanced Analytics Using Azure Machine Learning, Databricks, and the Lakehouse Architecture
- Big Data Analytics Using Azure Synapse Analytics
- Event-Driven Analytics Using Azure Event Hubs, Azure Stream Analytics, and Azure Machine Learning
- AI Using Azure Cognitive Services and Azure OpenAI

Über Autor(innen)

Deswandikar Aniruddha:
Aniruddha Deswandikar holds a Bachelor's degree in Computer Engineering and is a seasoned Solutions Architect with over 30 years of industry experience as a developer, architect and technology strategist. His experience spans from start-ups to dotcoms to large enterprises. He has spent 18 years at Microsoft helping Microsoft customers build their next generation Applications and Data Analytics platforms. His experience across Application, Data and AI has helped him provide holistic guidance to companies large and small. Currently he is helping global enterprises set up their Enterprise-scale Analytical system using the Data Mesh Architecture. He is a Subject Matter Expert on Data Mesh in Microsoft and is currently helping multiple Microsoft Global Customers implement the Data Mesh architecture.