Data Analytics for IT Networks: Developing Innovative Use Cases

Use data analytics to drive innovation and value throughout your network infrastructure

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.

• Understand the data analytics landscape and its opportunities in Networking
• See how elements of an analytics solution come together in the practical use cases
• Explore and access network data sources, and choose the right data for your problem
• Innovate more successfully by understanding mental models and cognitive biases
• Walk through common analytics use cases from many industries, and adapt them to your environment
• Uncover new data science use cases for optimizing large networks
• Master proven algorithms, models, and methodologies for solving network problems
• Adapt use cases built with traditional statistical methods
• Use data science to improve network infrastructure analysisAnalyze control and data planes with greater sophistication
• Fully leverage your existing Cisco tools to collect, analyze, and visualize data