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Network and IT professionals capture immense amounts of data from their networks. Buried in this data are multiple opportunities to solve and avoid problems, strengthen security, and improve network performance. To achieve these goals, IT networking experts need a solid understanding of data science, and data scientists need a firm grasp of modern networking concepts. Data Analytics for IT Networks fills these knowledge gaps, allowing both groups to drive unprecedented value from telemetry, event analytics, network infrastructure metadata, and other network data sources.Table of Contents:Chapter 1: Getting Started with Analytics\Chapter 2: Approaches for Analytics and Data ScienceChapter 3: Accessing Data from Network Components Chapter 4: Mental Models and Cognitive Bias Chapter 5: Innovative Thinking TechniquesChapter 6: Analytics Use Cases and the Intuition Behind ThemChapter 7: Analytics Algorithms and the Intuition Behind ThemChapter 8: Building Analytics Use CasesChapter 9: Developing Real Use Cases: The Power of StatisticsChapter 10: Developing Real Use Cases: Network Infrastructure AnalyticsChapter 11: Developing Real Use Cases: Control Plane Analytics Using Syslog TelemetryChapter 12: Developing Real Use Cases: Data Plane AnalyticsChapter 13: Cisco Analytics Chapter 14: Book Summary