Data Design Challenges for Enterprise IoT Applications
summary
Claim: prioritize a data-first design process because enterprise IoT data breaks common design assumptions. Concrete issues: fleets of 40–50,000 assets with 4–800 sensors each, mismatched sampling like 180,000 vs 5 samples when comparing high-frequency exhaust temperature to sparse throttle events, mixed units and missing metadata, and heavy integration/cleaning overhead. Tools used range from Illustrator for mockups to Excel, MATLAB or R for analysis; naive stacked y-axes and hover-only encodings fail to scale, so understand use case, scale, and architecture first.
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chapters (7)
- 0:00Introduction and background
- 3:24Designers and data challenges
- 8:20Data accessibility and integration
- 10:28Data-first design approach
- 15:46Design-first pitfalls in IoT
- 18:36Key assertions for data design
- 19:19Summary and Q&A
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