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Full Description
In the age of digital transformation, data is a strategic asset—but for many business leaders, it remains shrouded in technical jargon and complexity. This book simplifies modern data technologies into clear, accessible insights, specifically tailored for transformation leaders, department heads, and C-level executives. It empowers decision-makers to confidently align their data strategy with business objectives, unlock value from data investments, and lead with clarity in a data-driven world.
Part I of the book begins with an exploration of how businesses can become truly data-driven, highlighting the transition from legacy systems to modern, cloud-native data platforms. It breaks down essential components such as ingestion pipelines, storage solutions (data lakes, warehouses, lakehouses), integration tools, governance, compliance, and real-time vs. batch processing—explaining them with real-world relevance in the Microsoft Stack.
In Part II, you will learn how to build and mature an analytics strategy—from descriptive to prescriptive analytics. It explains Business Intelligence, data storytelling, user-driven dashboards, and methods to democratize insights across teams. Part III introduces traditional machine learning and generative AI, with frameworks for responsible AI, team building, and investment decisions. Part IV outlines a practical roadmap for building a data-first culture, measuring ROI, and future-proofing data strategy in the Microsoft ecosystem.
What You Will Learn:
Design a modern cloud-based data platform
Build analytics maturity in your organization
Integrate AI and Gen AI use cases into your business
Understand the ethical, regulatory, and operational considerations of AI
Build a sustainable data and analytics roadmap
Who This Book Is For:
Digital transformation and data strategy leaders
Contents
Part I: The Data-Driven Business Landscape.- Chapter 1: Introduction: Why Data Is Your Business Superpower.- Chapter 2: The Modern Data Stack in Microsoft: Explained Simply.- Chapter 3: Must-Have Cloud Data Components.- Chapter 4: The Role of the Business Leader in Data Strategy.- Part II: An Advanced Analytics Ecosystem.- Chapter 5: Advanced Analytics Roadmap Designing and Maximizing ROI.- Chapter 6: An Analytics Maturity Model.- Chapter 7: Data Storytelling and Democratizing Analytics within an Organization.- Part III: AI in Action.- Chapter 8: Traditional Machine Learning (Narrow AI).- Chapter 9: A Foundational Model/Generative AI.- Chapter 10: Responsible and Trustworthy AI in the World of AI Laws and Regulations.- Chapter 11: Framework for AI Use Case Selection and Maximizing ROI.- Part IV: Strategy, Culture, Execution, and Future-Proof Next Steps.- Chapter 12: Data Culture and Literacy.- Chapter 13: The Data and AI Roadmap.- Chapter 14: Conclusion: Leading with Data Confidence.- Appendix A: References.
