Drowning in alerts but unsure which ones actually reduce risk? Security teams face an overwhelming flood of data every day, yet it is often unclear which signals matter and how to act on them. Without a structured way to prioritize threats and communicate their impact, even the best analysts struggle to protect their organization. What if you could turn noise into insight and confidently direct resources where they matter most? By aligning metrics with business goals and using real-time data effectively, you can cut through uncertainty and build measurable, trusted security operations.
Data-Driven Cybersecurity by veteran CISO Mariano Mattei delivers a complete, format-agnostic field guide to measurable security.
Mattei introduces ATLAS, a step-by-step framework that aligns metrics with business goals and reduces alert fatigue. Hands-on chapters walk you through building dashboards, feeding models, and integrating AI tools, all backed by industry examples. Finish the book able to defend budgets, justify hires, and close gaps with quantifiable proof. Replace gut feelings with dashboards that speak for themselves. Perfect for security analysts, SOC leads, and managers who already know basics and crave actionable, numbers-first guidance.
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Mariano Mattei is a VP of Cybersecurity and AI, known for turning data into proactive protection. With three decades in software engineering and C-suite security roles, Mariano brings clear, tool-driven guidance to every page. He distills deep expertise into repeatable frameworks that let readers prove value and cut risk.
From the back cover:
Data-Driven Cybersecurity shows you the metrics, data, and KPIs that will help you assess and enhance the performance of your cyber security programs. You'll learn how to turn complex metrics into actionable security practices, following the unique ATLAS (Alert Threshold Lifecycle Assessment System) methodology created by author Mariano Mattei. You'll go hands-on to build a real-time threat detection dashboard, and discover how AI and machine learning can proactively predict cybersecurity incidents. Case studies, interactive exercises, templates for KPIs, and expert insights help illustrate each new concept.
About the reader:
For readers familiar with the basics of cyber security and data analysis.
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Paperback. Zustand: New. Drowning in alerts but unsure which ones actually reduce risk? Security teams face an overwhelming flood of data every day, yet it is often unclear which signals matter and how to act on them. Without a structured way to prioritize threats and communicate their impact, even the best analysts struggle to protect their organization. What if you could turn noise into insight and confidently direct resources where they matter most? By aligning metrics with business goals and using real-time data effectively, you can cut through uncertainty and build measurable, trusted security operations. ATLAS methodology: Turns scattered alerts into a lifecycle that prioritizes real threats. Metric templates: Generate clear KPIs your executives understand, fund, and track. Real-time dashboards: See live threat detection and performance on one screen, not ten. AI and machine learning: Predict incidents before attackers move, using practical code samples. Case studies and exercises: Apply lessons immediately to biotech, pharma, and any regulated industry. Visualization techniques: Present results visually so decisions happen fast. Data-Driven Cybersecurity by veteran CISO Mariano Mattei delivers a complete, format-agnostic field guide to measurable security. Mattei introduces ATLAS, a step-by-step framework that aligns metrics with business goals and reduces alert fatigue. Hands-on chapters walk you through building dashboards, feeding models, and integrating AI tools, all backed by industry examples. Finish the book able to defend budgets, justify hires, and close gaps with quantifiable proof. Replace gut feelings with dashboards that speak for themselves. Perfect for security analysts, SOC leads, and managers who already know basics and crave actionable, numbers-first guidance. Bestandsnummer des Verkäufers LU-9781633436107
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