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Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe.
This talk covers:
Common components of an IoT solution
The challenges involved with managing time-series data in IoT applications
Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance.
How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts
At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.