Modeling, Querying and Seeing Time Series Data within a Self-Organizing Mesh Network

Explore the intricacies of modeling, querying, and visualizing time series data within self-organizing mesh networks in this comprehensive conference talk by Denise Gosnell, Chief Data Officer at DataStax. Dive deep into the world of graph data and its applications in the power industry, focusing on how graph databases can be used to model dynamic networks within power grids. Learn how to build a graph database that represents the communication network between sensors and call towers, and discover how this structure aids in real-time monitoring of network status and failure scenarios. Through a hands-on notebook environment, examine the code for database modeling and graph database queries, and understand how to apply path information to identify at-risk network sensors. Gain valuable insights into the role of graph data structures in network healing processes and explore the concept of "social fingerprinting" in predicting user identity from social media interactions. Access the provided GitHub repository to further experiment with the data and code presented in this informative session.

Denise Gosnell -Modeling, Querying and Seeing Time Series Data within a Self-Organizing Mesh Network