The Data Officer's Field Guide
Leadership and Lifecycle for Data Strategy, Governance, Analytics, and Responsible AI
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Beschreibung
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.
Leadership field guide uniting data strategy, governance, analytics, responsible AI, and measurable KPIs Lifecycle execution playbook for operating models, budgets, roles, and ROI at enterprise scale Pragmatic guidance on data mesh, generative AI, and interoperability aligned to outcomes
Autor*in
Vyasaraj Raghavendra
Themen in »The Data Officer's Field Guide«
chief data officer data strategy enterprise data strategy data governance framework data platform architecture data engineering pipelines data lakehouse architecture mlops for production generative ai governance responsible ai practices data quality management data compliance and privacy data modeling best practices etl and elt pipelines data observability