Data Analytics for IT Networks: Developing Innovative Use Cases

Data analytics can drive innovation and value throughout your network infrastructure by bridging the knowledge gap between IT networking experts and data scientists. John Garrett's book provides practical guidance on how to uncover innovative use cases by integrating data science algorithms with network data, using Python-based case studies to demonstrate real-world applications.

\n Format: Paperback / softback
\n Length: 496 pages
\n Publication date: 17 January 2019
\n Publisher: Pearson Education (US)
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Network and IT professionals generate vast amounts of data from their networks, containing numerous potential solutions to problems, enhancing security, and improving network performance. To achieve these objectives, IT networking experts require a strong foundation in data science, while data scientists need to comprehend modern networking concepts.

Data Analytics for IT Networks bridges these knowledge gaps, enabling both groups to extract maximum value from telemetry, event analytics, network infrastructure metadata, and other network data sources. Drawing on his extensive experience in applying data science to large-scale Cisco networks, John Garrett provides the specific methodologies and algorithms required by network and IT professionals, while also helping data scientists understand contemporary network technologies, applications, and data sources.

After establishing a common understanding, Garrett showcases how to identify innovative use cases that integrate data science algorithms with network data. He concludes with practical case studies, implemented in Python, demonstrating how Cisco Customer Experience (CX) engineers support its largest customers. These case studies serve as templates for developing custom solutions, ranging from advanced troubleshooting to service assurance.

In this comprehensive guide, you will gain a deep understanding of the data analytics landscape and its opportunities in networking. You will explore the components of an analytics solution and see how they come together in practical use cases. You will also learn how to access network data sources and choose the right data for your specific problem. By understanding mental models and cognitive biases, you will enhance your ability to innovate more successfully. Finally, you will walkthrough common analytics use cases, covering various aspects of network management and optimization.

\n Weight: 871g\n
Dimension: 230 x 190 x 20 (mm)\n
ISBN-13: 9781587145131\n \n