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Microsoft Adds Root Cause Analysis and Time Exploration Updates to Azure Time Series Insights

| by Kent Weare Follow 7 Followers on Aug 13, 2017. Estimated reading time: 2 minutes |

This past April, Microsoft announced updates to their Azure Internet of Things (IoT) platform. One of the announcements that InfoQ has been tracking includes the emergence of Azure Time Series Insights (TSI). The purpose of this service includes the ability for customers to discover and manage their device telemetry across a time series.

Time series data is nothing new in industries such as manufacturing, oil and gas, utilities, transportation and mining. However, traditional solutions have depended upon on-premises deployments of historian technology that had relied upon fixed pricing models. Having the ability to use consumption-based cloud services to store and analyze device data has been gaining traction. iSolutions, an industrial operational technology (OT) consulting firm has identified some benefits they are experiencing with their customers by using cloud-based services:

Drivers of this trend [cloud-based time series data services] include cost considerations, a desire to access cloud-based analytics capabilities (e.g. streaming queries and notifications, machine learning, cloud-based business intelligence, etc.) and in some cases, performance limitations of existing on-premise data historians.

Microsoft’s Time Series Insights service is currently in public preview and Microsoft has recently added some new features including Root Cause Analysis and updates to Time Exploration.

Azure Time Series Insights is able to consume massive amounts of data, which at times create “signal to noise” challenges. OP Ravi, a principal program manager at Microsoft explains:

Time Series Insights is a fully managed analytics, storage, and visualization service that makes it simple to explore and analyze billions of IoT events simultaneously. We’ve heard a lot of feedback from our manufacturing, and oil and gas customers that would like to conduct root cause analysis and investigations, but it’s been difficult for them to quickly pinpoint statistically significant patterns in their data. To make this process more efficient, we’ve added a feature that proactively surfaces the most statistically significant patterns in a selected data region. This relieves users from having to look at thousands of events to understand what patterns most warrant their time and energy.

Microsoft has also made it easy for customers to jump directly to these significant data patterns. Microsoft feels that this feature will help organizations reduce the triage time required during post-mortem investigations.

Another area where Microsoft has invested in is providing customers with greater control over data exploration. Ravi explains:

We have heard from customers across many verticals that they are using Time Series Insights to help them triage and diagnose issues involving sensor data from their key assets, but they have been asking for finer control over their ability to navigate time in our visualizations. To give these customers more control, we have provided several new usability improvements to time navigation to make triage and diagnosing easier.

More specifically, a time interval slider has been included to allow for navigating large slices of time series data, right down to the millisecond. In addition, Microsoft will set the default starting point to include the most optimal view of the data from a user’s selection. This feature allows customers to find their answer quickly, while balancing resolution, query speed and granularity.

Image Source: https://azure.microsoft.com/en-us/blog/root-cause-analysis-and-time-exploration-updates-to-azure-time-series-insights/

Azure Time Series Insight is currently in public preview, but anyone with a Microsoft Azure account can access a free demo environment where they can explore these features and capabilities.

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