The Data Officer's Field Guide : Leadership and Lifecycle for Data Strategy, Governance, Analytics, and Responsible AI
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Overview
Turn strategy into results: align data strategy, governance, analytics, and responsible AI with the right operating models and KPIs to scale confidently.
This vendor-neutral field guide helps chief data officers and data leaders set a clear mandate, design the organization, plan budgets and ROI, and run programs that deliver measurable outcomes. It emphasizes trust by design - governance, quality, privacy, compliance, and security - embedded throughout the lifecycle rather than bolted on at the end.
Grounded in practical leadership and execution, the book moves from mandate and roadmap to delivery mechanics: architecture choices that scale, analytics and BI for decision-making, responsible AI and automation, turning data into reusable assets and revenue, and risk controls that keep value and trust aligned. Readers get concise, decision-ready frameworks and trade-offs they can apply across centralized, federated, mesh, or hybrid operating models without drifting into tool-chasing.
What You Will Learn
- Craft and execute a scalable, business-aligned data strategy with clear outcomes and ROI
- Design and lead a high-performing data organization with budgets, roles, and accountability
- Embed governance, quality, privacy, and security as trust by design across the lifecycle
- Choose and evolve operating models (centralized, federated, mesh, hybrid) for delivery at scale
- Communicate value to executives with KPI instrumentation, ROI narratives, and board-ready storytelling
- Link architecture choices and roadmaps to measurable outcomes and risk controls
- Turn data into reusable assets and revenue while maintaining compliance and interoperability
- Anticipate trends such as data mesh, generative AI, interoperability, and open data ecosystems and apply them pragmatically
Who this Book Is for
Chief data officers; heads of data; data architects; engineering managers; CIOs/CTOs; product managers; AI/ML engineers; cloud/DevOps professionals seeking a vendor-neutral, leadership-and-lifecycle guide to data strategy, governance, analytics, and responsible AI.
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Details
- ISBN-13: 9798868832864
- ISBN-10: 9798868832864
- Publisher: Apress
- Publish Date: March 2027
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