Harnessing Microsoft Fabric and Azure Service Fabric Analytics as a Service and Enterprise Solutions.pdf
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Understand the key capabilities of Microsoft Fabric Services and how they offer solutions for today's data and analytics needs. https://dynatechconsultancy.com/microsoft-fabric
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Harnessing Microsoft Fabric and Azure Service Fabric Analytics as a Service and Enterprise Solutions.pdf
- 1. 2 Microsoft Fabric Analytics-as-a-Service in den Zeiten von KI Hans-Peter Bareiner Practice Lead – Azure Analytics Platform - Germany Azure Service Fabric
- 2. How do you translate data into competitive advantage?
- 3. AI is causing a massive platform shift
- 4. But AI is only as good as your data
- 5. Challenges to realizing your data strategy Multiple factors create a complex barrier to delivering value from data. Limited data governance Difficult to balance access and data protection Data quality Rapidly increasing data volumes Security and compliance risks Disparate systems and data silos Slow time to value Insufficient data literacy and expertise Proliferation of data solutions Shadow IT Limited scalability Complex integrations
- 6. Unlock business value with a modern data platform Create the foundation for a progressive data strategy and innovative analytics solutions. Data-driven business insights Holistic data, management, and analytics Robust governance that enables access and flexibility Secure, compliant, and fully integrated Well-architected, repeatable, modular patterns
- 7. Develop and optimize a data strategy and platform Leverage the data management and analytics scenario for best practices and executable resources. CLOUD SCALE ANALYTICS SCENARIO Deployment templates Deploy infrastructure and create new resources with repeatable templates and declarative syntax. Assessments Identify gaps in governance, evaluate workload performance, understand your DevOps capabilities, and more. Well-Architected Framework Follow key principles of architectural excellence to guide workload development and optimization. Skilling resources Map the skills needed to drive your data strategy to your existing capabilities. Build new skills through learning resources and certifications. Cloud Adoption Framework Align business and technical strategies for the cloud using Microsoft guidance, best practices, documentation, and tools. Reference architectures Leverage modular building blocks to grow your infrastructure over time and adapt the scenario to your use cases.
- 8. Empower teams by facilitating data self-service Increase data agility and accelerate time to value. Platform (Shared Services) Azure Synapse Azure Purview Data Lake Platform (Shared Services) Competing business needs Workarounds to enable agility Centralized architectures Improves quality and security Increases efficiency and access Common governance and management Resource: Build an initial strategy Centralized data ownership IT centrally owns data and all services Federated data ownership Business owns data-driven projects
- 9. Prepare for agile data management Enabling self-service at scale requires a holistic approach to data management. Resource: Prepare your environment Enforce data governance and security. → Serve data as a product rather than a byproduct. → Provide an ecosystem of data products instead of a single data warehouse. → Create data domains to serve lines of business. → Empower teams to drive analytics solutions that deliver value to the business. → Modernize your teams and operations. → Prepare your company to:
- 10. Evolution of Data Architectures with Microsoft Fabric
- 11. Every analytics project has many subsystems Every subsystem need a different class of product Products often comes from multiple vendors Integration at scale across products is complex, fragile and expensive Scalable analytics are complex and fragmented
- 12. Massive fragmentation of the modern data stack
- 13. The 2023 ML, AI, and Data Landscape
- 14. Simplify, I am the Chief Data Officer and don’t want to be the Chief Integration Officer.” Every CDO, Every Enterprise “
- 15. Azure AI Purview Data Factory Synapse Spark Power BI Kusto Synapse DW Our Simplification Approach From a collection of products, to… Data Integration Data Warehouse Real Time Analytics Business Intelligence Data Science Data Lake Governance Spark Engines Unified analytics fabric Built on open standards
- 16. Announcing Microsoft Fabric Data analytics for the era of AI
- 17. AI Powered Copilot accelerated GPT on your data AI-driven insights Microsoft Fabric Data analytics for the era of AI Complete Analytics Platform Everything, unified SaaS-ified Secured and governed Lake Centric and Open OneLake One copy Open at every tier Empower Every Business User Familiar and intuitive Built into Microsoft 365 Insight to action
- 18. Microsoft Fabric Data analytics for the era of AI OneLake Data Factory Synapse Data Engineering Synapse Data Science Synapse Data Warehouse Synapse Real Time Analytics Power BI Data Activator
- 20. SaaS “It just works" Frictionless onboarding Quick results w/ Intuitive UX Instant provisioning 5x5 Minimal knobs Auto optimized Auto integrated Success by default Tenant-wide governance Centralized security management Compliance built-in Centralized administration
- 21. OneLake for all your Data “The OneDrive for Data” OneDrive for documents OneLake for data OneLake provides a data lake as a service without you needing to build it
- 22. OneLake for all domains A true hub & spoke data mesh across organizational data domains. Workspaces and artifacts for different data domains, contribute to building the same data lake. Without data movement, data from different domains can be analyzed, blended and transformed together. Data is secured and governed in one place while remaining easily discoverable and accessible to all who should have access across the organization. Data can be certified by domain experts to enabling trust for data which is discovered. Marketing HR Operations Finance Customer Sales IT OneLake
- 23. Available today Try Fabric yourself aka.ms/try-fabric Microsoft Fabric
- 24. 25 SESSION FEEDBACK https://aka.ms/AzSum-S012 Session Title: Analytics-as-a-Service in Zeiten von KI