Updates to Azure Time Series Insights simplify analysis of IoT data

 |   Microsoft IoT

Patterns in the Time Series Insights stats tab and addition of a pattern as a new term.

The unprecedented volume of data generated by the Internet of Things (IoT) has made analysis of time-series data a powerful way to gain actionable insights into business performance. This type of analytics can help companies uncover hidden trends, conduct root-cause analyses, and quickly validate IoT solutions.

Yet collecting, managing, visualizing, and analyzing time-series data at scale and in near-real time is a tall order for even the most capable of companies. That’s because sensors and connected devices can generate billions of data points every day, and businesses lack a centralized view of data and the ability to perform a unified query. Combining and visualizing disparate data types—in particular, time-series data and reference data—is daunting because organizations typically use multiple, non-integrated tools and techniques.

Microsoft is addressing these challenges in a new update to the public preview of Azure Time Series Insights, a managed cloud service that provides a global view of IoT-scale data with real-time visibility into time-series data across all locations. Updates to Time Series Insights include:

  • Streamlined management of time-series data in the Azure Portal.
  • Documentation on reference data API that makes it easier to combine time-series data with more static reference and historical data—and build custom solutions.
  • A dynamic search span that allows businesses to customize and run repeatable queries using a single template, as well as use relative time spans in queries.
  • A new feature that surfaces statistically significant patterns and enables users to quickly perform root-cause analyses and post-mortem investigations.
  • Several new usability improvements to time navigation that help streamline triage and diagnosis.
  • A time brush tool that makes it easier to move between time ranges when diagnosing sensor data.
  • Updates to the JSON data interchange format that add the ability to import multi-content JSON payloads.
A GIF showing patterns in the Time Series Insights stats tab and addition of a pattern as a new term.
A GIF showing patterns in the Time Series Insights stats tab and addition of a pattern as a new term.

One company that’s benefiting from Microsoft’s IoT solutions is EcoLab, a leading provider of water and energy services that is creating a system to help its industrial customers reduce water use. Leveraging the Azure IoT Suite, EcoLab has combined approximately 10TB of time-series data like water use with sales and other data to help visualize and identify patterns. Azure has helped the company address an inherent IoT challenge: The ability to combine and analyze time-series data from operations processes around the world.

Microsoft will continue to update and add functionality to Time Series Insights while in public preview. To find out more about how we are building the leading platform for analyzing time-series data, read our blog post announcing new Time Series Insights capabilities. You can also register for our upcoming webinar, “Quickly unlock insights hidden in your time series data,” on September 19, 2017 from 10:00-11:00 a.m. PDT .

Tags: , ,