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Home > Computing and Information Technology > Computer networking and communications > Network management > Data Analytics for IT Networks: Developing Innovative Use Cases(Networking Technology)
Data Analytics for IT Networks: Developing Innovative Use Cases(Networking Technology)

Data Analytics for IT Networks: Developing Innovative Use Cases(Networking Technology)


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About the Book

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. Drawing on his pioneering experience applying data science to large-scale Cisco networks, John Garrett introduces the specific data science methodologies and algorithms network and IT professionals need, and helps data scientists understand contemporary network technologies, applications, and data sources. After establishing this shared understanding, Garrett shows how to uncover innovative use cases that integrate data science algorithms with network data. He concludes with several hands-on, Python-based case studies reflecting Cisco Customer Experience (CX) engineers’ supporting its largest customers. These are designed to serve as templates for developing custom solutions ranging from advanced troubleshooting to service assurance.

Table of Contents:
Chapter 1 Getting Started with Analytics Chapter 2 Approaches for Analytics and Data Science Chapter 3 Understanding Networking Data Sources Chapter 4 Accessing Data from Network Components Chapter 5 Mental Models and Cognitive Bias Chapter 6 Innovative Thinking Techniques Chapter 7 Analytics Use Cases and the Intuition Behind Them Chapter 8 Analytics Algorithms and the Intuition Behind Them Chapter 9 Building Analytics Use Cases Chapter 10 Developing Real Use Cases: The Power of Statistics Chapter 11 Developing Real Use Cases: Network Infrastructure Analytics Chapter 12 Developing Real Use Cases: Control Plane Analytics Using Syslog Telemetry Chapter 13 Developing Real Use Cases: Data Plane Analytics Chapter 14 Cisco Analytics Chapter 15 Book Summary Appendix A Function for Parsing Packets from pcap Files

About the Author :
John Garrett is CCIE Emeritus (6204) and Splunk Certified. He earned an M.S. in predictive analytics from Northwestern University, and has a patent pending related to analysis of network devices with data science techniques. John has architected, designed, and implemented LAN, WAN, wireless, and data center solutions for some of the largest Cisco customers. As a secondary role, John has worked with teams in the Cisco Services organization to innovate on some of the most widely used tools and methodologies at Customer Experience over the past 12 years. For the past 7 years, John’s journey has moved through server virtualization, network virtualization, OpenStack and cloud, network functions virtualization (NFV), service assurance, and data science. The realization that analytics and data science play roles in all these brought John full circle back to developing innovative tools and techniques for Cisco Services. John’s most recent role is as an Analytics Technical Lead, developing use cases to benefit Cisco Services customers as part of Business Critical Services for Cisco. John lives with his wife and children in Raleigh, North Carolina.


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Product Details
  • ISBN-13: 9781587145131
  • Publisher: Pearson Education (US)
  • Publisher Imprint: Cisco Press
  • Height: 230 mm
  • No of Pages: 496
  • Series Title: Networking Technology
  • Sub Title: Developing Innovative Use Cases
  • Width: 190 mm
  • ISBN-10: 1587145138
  • Publisher Date: 24 Jan 2019
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Spine Width: 30 mm
  • Weight: 921 gr


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