The TempoIQ Blog

Analyzing Sensor Data with TempoIQ - Aggregation

Posted by Sam Johnson on 10/22/14

In our last post, we covered how rollups can summarize information across one stream of data. While you can learn a lot from a single stream, you can gain more insight and visibility into your devices by aggregating information across devices. By looking at the average temperature across a building, or the max power output from a solar field, you can benchmark performance or look for the root cause of historical anomalies.

To help you get a better picture of what’s happening across sensors and devices, we’ve built a feature called aggregation.

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How Quickly Will IoT Impact Your Industry?

Posted by Sam Johnson on 10/15/14

The IoT World Forum is this week in Chicago, and TempoIQ is there in force. There are some amazing keynotes today (which you can watch live on their site), but there was one moment at the beginning of the day that really stuck with us.

The organizers of the IoT World Forum asked the attendees a few survey questions to take the pulse of the group and get a sense for where IoT was headed. One of the questions we found particularly intereresting was "which vertical is most likely to adopt IoT faster?"

Today we got the answer:

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Analyzing Sensor Data with TempoIQ - Rollups

Posted by Sam Johnson on 10/9/14

There are many different ways to manipulate time series data for analysis and visualization. In the case of sensor data, companies typically record data at very short intervals - a minute or less - but want to read it back in longer intervals - 5 minutes, 10 minutes, or longer. While storing their information with high granularity provides a lot of flexibility, companies still need a way to summarize this data.

To help companies manage this data transformation, our analytics engine has a feature called rollups.

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Analyzing Sensor Data with TempoIQ - Interpolation

Posted by Sam Johnson on 10/2/14

There are numerous types of analysis you can do on time-series data. We offer the ability to interpolate, roll-up, and aggregate over a stream of data in what we call the analytics pipeline. Over the next few posts, we’ll cover what each of these functions do and show how they all come together to allow you to perform complex analysis in your analytics pipeline.

Today, we’re going to talk about the first step many people take in time-series and sensor data analysis - interpolation.

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The Array of Things and Chicago as a Data Platform

Posted by Sam Johnson on 10/1/14

The goal of the Internet of Things is to give us a more nuanced understanding of the world. We put devices and sensors on us and around to us to gather information that will help us make better decisions and, hopefully, live better lives. To that end, we are always looking for projects that help the world get there faster.

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How Much Data Will Your Sensor Analytics Application Generate?

Posted by Sam Johnson on 9/25/14

 

The scale of sensor analytics is well understood. According to Cisco's research, there will be 50 billion connected devices by 2020. Each of these devices will be sending off sensor data between once a minute and once a second, which adds up to a huge amount of data each year. It's an interesting macro trend, but what does it mean for your business?

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Why TempoIQ Moved Off HBase

Posted by Sam Johnson on 9/18/14

When we decided to shift from time series storage to sensor analytics, we not only revamped our product, but we also revisited our backend architecture. One of the critical aspects we looked closely at was our storage layer. In our previous system, we used HBase for data storage. HBase is a distributed big data store in the Apache Hadoop family, a set of projects that provides tools for reliable, scalable, distributed computing.

After evaluating our options, we decided to build a proprietary data store instead of continuing with HBase. It didn’t fit in with our architecture goals, and we wanted to address some of the issues we’d seen writing, storing and reading large-scale sensor data.

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TempoIQ Named Top 10 Hot IoT Startup by CIO.com

Posted by Sam Johnson on 9/15/14

Earlier this month, we were named one of 10 hot Internet of Things startups by CIO.com. On our journey to make sense of the measured world, it’s great to see that other people in the industry understand both the challenges and value of analyzing large scale sensor data in realtime. We’re excited to be a part of such a promising group of companies.

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Building or Buying a Sensor Analytics Infrastructure - Part 2, Technical Considerations

Posted by Sam Johnson on 9/11/14

This is part 2 in a 2-part series on considerations to make when building or buying a sensor analytics backend.

In our last post, we talked about business and strategic considerations when building or buying a sensor analytics backend. Answering those questions is critical to making an informed decision, but there are still many executional and technical considerations beyond that. In this post, we focus on those aspects of the build vs. buy decision.

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Building or Buying a Sensor Analytics Infrastructure - Part 1, Business Considerations

Posted by Sam Johnson on 9/8/14

This is part 1 in a 2-part series on considerations to make when building or buying a sensor analytics backend.

Building a sensor analytics application is a major undertaking for most organizations. It’s typically a shift in the way they do business, whether they are adding a smart product or augmenting an existing offering.

It’s also a complex initiative, and the management team has to make decisions from hardware to connectivity to backend infrastructure to application development. One of the major debates with each of these components is to build or to buy. Is a company going to build it’s own hardware, or source it from a device company? Are they building their own sensor analytics backend, or are they going to purchase a service? Are they developing the end-user application, or are they hiring a firm to develop it?

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