Azure Time Series Insights—New capabilities to derive more insights from IoT data
Updated: November 04, 2019
Azure Time Series Insights has new capabilities that will help organizations to derive insights from their IoT data. Building upon our rich visualization tools and extensive analytic capabilities, the new features in Time Series Insights will help companies detect and diagnose anomalies and drive operational efficiency with IoT data.
The following new features are available in your preview environment:
- Multilayered storage with warm and cold analytics support. This will provide both interactive analytics over short timespans as well as operational intelligence over decades of historical data.
- Support for discrete signal processing in order to analyze sensors sending categorical state data, for example, "on/off" or "good/bad".
- Connect with common computation technologies such as Databricks, Jupyter, predictive analytics, and machine learning tools with our open source Apache Parquet data storage.
- Supports the growing demand for IoT insights with a higher capacity for concurrent queries.
- Signal interpolation intelligently reconstructs missing data for a complete picture of the situation.
- Scatterplot graphs broaden your visualization capabilities.
- Quickly compare variables across different time spans for faster anomaly diagnosis.
- The native Power BI connector enhances IoT data allowing you to analyze it next to other business data.
New search and navigation APIs are now available for custom integrations.
Learn more in our documentation.