Data Engineering Podcast


This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.

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30 July 2018

Mobile Data Collection And Analysis Using Ona And Canopy With Peter Lubell-Doughtie - Episode 41 - E41

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Summary

With the attention being paid to the systems that power large volumes of high velocity data it is easy to forget about the value of data collection at human scales. Ona is a company that is building technologies to support mobile data collection, analysis of the aggregated information, and user-friendly presentations. In this episode CTO Peter Lubell-Doughtie describes the architecture of the platform, the types of environments and use cases where it is being employed, and the value of small data.

Preamble

  • Hello and welcome to the Data Engineering Podcast, the show about modern data management
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  • Go to dataengineeringpodcast.com to subscribe to the show, sign up for the mailing list, read the show notes, and get in touch.
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  • Your host is Tobias Macey and today I’m interviewing Peter Lubell-Doughtie about using Ona for collecting data and processing it with Canopy

Interview

  • Introduction
  • How did you get involved in the area of data management?
  • What is Ona and how did the company get started?
    • What are some examples of the types of customers that you work with?


  • What types of data do you support in your collection platform?

  • What are some of the mechanisms that you use to ensure the accuracy of the data that is being collected by users?

  • Does your mobile collection platform allow for anyone to submit data without having to be associated with a given account or organization?

  • What are some of the integration challenges that are unique to the types of data that get collected by mobile field workers?

  • Can you describe the flow of the data from collection through to analysis?

  • To help improve the utility of the data being collected you have started building Canopy. What was the tipping point where it became worth the time and effort to start that project?

    • What are the architectural considerations that you factored in when designing it?
    • What have you found to be the most challenging or unexpected aspects of building an enterprise data warehouse for general users?


  • What are your plans for the future of Ona and Canopy?

Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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