Secure Data Intelligence Guide by Amsel Leon (3 results)

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condition: new. Paperback. Secure Data Intelligence Guide: A Practical Blueprint for Protecting Analytical Pipelines in the Age of AI, Automation, and Cloud-Scale DataBy Leon AmselData is moving faster than ever, and so are the threats targeting it. As organizations rely on analytics, machine learning, and automated decision systems, one question becomes unavoidable: How do you protect analytical pipelines that never stop running? This book answers that challenge with a clear, modern, and highly actionable framework built for today's cloud-scale world.Secure Data Intelligence Guide gives readers a complete, practical system for defending data pipelines from ingestion to reporting, modeling, and beyond. Rather than relying on abstract concepts or outdated security checklists, it introduces concrete patterns that fit naturally into real engineering workflows. If you work with AI-driven analytics, cloud data warehouses, streaming platforms, or high-volume reporting systems, this book delivers the playbook you've been missing.You will learn how to recognize hidden exposure points in modern pipelines, apply effective security controls without slowing innovation, and establish a defensible, audit-ready analytics ecosystem. Every chapter focuses on practical decisions, how to secure ingestion, protect transformations, manage warehouse access, monitor for threats, and safely operationalize machine learning models.Readers will gain the ability to: - Strengthen ingestion systems using identity controls, validation, and secure connectors.- Protect transformations with workflow isolation, secrets management, and role architecture.- Harden cloud warehouses with encryption, masking strategies, and granular access controls.- Safeguard dashboards, BI tools, and exports with governed sharing and precise permissions.- Defend machine learning pipelines against poisoning, drift, prompt leakage, and model misuse.- Build monitoring and incident response practices tailored to analytics environments.- Establish long-term governance using Zero Trust, automation, and forward-looking controls.This book is perfect for data engineers, analytics leaders, security teams, and ML practitioners seeking practical, scalable strategies for the modern era. It speaks directly to the realities of AI, automation, cloud-native architectures, and the rising stakes of data protection.If you want a proven, field-tested blueprint for securing analytical operations, and you're ready to strengthen the systems your organization depends on, start reading today and bring your analytics environment to a professional, defensible standard. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condition: new. Paperback. Secure Data Intelligence Guide: A Practical Blueprint for Protecting Analytical Pipelines in the Age of AI, Automation, and Cloud-Scale DataBy Leon AmselData is moving faster than ever, and so are the threats targeting it. As organizations rely on analytics, machine learning, and automated decision systems, one question becomes unavoidable: How do you protect analytical pipelines that never stop running? This book answers that challenge with a clear, modern, and highly actionable framework built for today's cloud-scale world.Secure Data Intelligence Guide gives readers a complete, practical system for defending data pipelines from ingestion to reporting, modeling, and beyond. Rather than relying on abstract concepts or outdated security checklists, it introduces concrete patterns that fit naturally into real engineering workflows. If you work with AI-driven analytics, cloud data warehouses, streaming platforms, or high-volume reporting systems, this book delivers the playbook you've been missing.You will learn how to recognize hidden exposure points in modern pipelines, apply effective security controls without slowing innovation, and establish a defensible, audit-ready analytics ecosystem. Every chapter focuses on practical decisions, how to secure ingestion, protect transformations, manage warehouse access, monitor for threats, and safely operationalize machine learning models.Readers will gain the ability to: - Strengthen ingestion systems using identity controls, validation, and secure connectors.- Protect transformations with workflow isolation, secrets management, and role architecture.- Harden cloud warehouses with encryption, masking strategies, and granular access controls.- Safeguard dashboards, BI tools, and exports with governed sharing and precise permissions.- Defend machine learning pipelines against poisoning, drift, prompt leakage, and model misuse.- Build monitoring and incident response practices tailored to analytics environments.- Establish long-term governance using Zero Trust, automation, and forward-looking controls.This book is perfect for data engineers, analytics leaders, security teams, and ML practitioners seeking practical, scalable strategies for the modern era. It speaks directly to the realities of AI, automation, cloud-native architectures, and the rising stakes of data protection.If you want a proven, field-tested blueprint for securing analytical operations, and you're ready to strengthen the systems your organization depends on, start reading today and bring your analytics environment to a professional, defensible standard. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.