How to Build an IoT Data Lake
The Internet of Things (IoT) is one of the driving forces for the increase in today’s data volume and diversity. IoT platforms must enable users to leverage incoming data for immediate analysis/action as well as long-term historical analytics. For the latter, the data needs to be stored efficiently and made available for large-scale analytics.
This talk discusses both the challenges and solutions of using data lakes for long-term storage of IoT data, including:
- How data is moved from the IoT platform to the data lake
- How data is organized
- How efficient querying by consumers (e.g., IoT platform user interface, business intelligence tools and machine learning applications) is achieved
Speakers
Chris Furlong
Chris Furlong is an experienced, versatile, and commercially astute IT leader with extensive expertise in product management and marketing, product development and pre-sales consultancy. Chris is focused on business intelligence, analytics, and data management technologies and is currently working in various areas of IoT.
Tim Doernemann
Tim Doernemann graduated with a degree in computer science from the University of Marburg, Germany, in 2006. During his doctoral program at the Distributed Systems Research Group of University of Marburg he worked on various topics around scheduling and quality of service for high-performance computing, grid computing and cloud computing applications. Since 2012, he has workeds as a developer and architect at the intersection of IoT and data analytics.
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