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Data analytics for IT networks : developing innovative use cases / John Garrett, CCIE Emeritus No. 6204, MSPA.

By: Publisher: San Jose, CA : Cisco Press, 2019Description: xxiv, 472 pages : illustrations ; 23 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781587145131
Subject(s): DDC classification:
  • 23 004.6 G19 2019
Contents:
Introduction: Your future is in your hands! Getting Started with Analytics Approaches for Analytics and Data Science Understanding Networking Data Sources Accessing Data from Network Components Mental Models and Cognitive Bias Innovative Thinking Techniques Analytics Use Cases and the Intuition Behind Them Analytics Algorithms and the Intuition Behind Them Building Analytics Use Cases Developing Real Use Cases: The Power of Statistics Developing Real Use Cases: Network Infrastructure Analytics Developing Real Use Cases: Control Plane Analytics Using Syslog Telemetry Developing Real Use Cases: Data Plane Analytics Cisco Analytics Book Summary Appendix A: Function for Parsing Packets from pcap Files
Summary: 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. -- Provided by publisher
Holdings
Item type Current library Collection Call number Status Barcode
Books Books College Library General Circulation Section GC GC 004.6 G19 2019 (Browse shelf(Opens below)) Available HNU004837

Includes index.

Introduction: Your future is in your hands!
Getting Started with Analytics
Approaches for Analytics and Data Science
Understanding Networking Data Sources
Accessing Data from Network Components
Mental Models and Cognitive Bias
Innovative Thinking Techniques
Analytics Use Cases and the Intuition Behind Them
Analytics Algorithms and the Intuition Behind Them
Building Analytics Use Cases
Developing Real Use Cases: The Power of Statistics
Developing Real Use Cases: Network Infrastructure Analytics
Developing Real Use Cases: Control Plane Analytics Using Syslog Telemetry
Developing Real Use Cases: Data Plane Analytics
Cisco Analytics
Book Summary
Appendix A: Function for Parsing Packets from pcap Files

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. --

Provided by publisher

College of Engineering and Computer Studies Bachelor of Science in Information Technology

In English

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