Is data from your IoT devices being sold to third parties?
Is the digital divide over consumer data widening? How can smart data be leveraged for business success? What data spawned the current AI boom?
Is data from your IoT devices being sold to third parties? 🏠 Reportedly, Colin Angle, the CEO of iRobot (the maker of robotic vacuum Roomba), suggested that they might start selling information on the layout of your home to Amazon, Alphabet, or Apple - to help enhance the "smart" home. 😱 Later in the week, however, Angle claimed his previous statements were misinterpreted and that "iRobot will never sell your data" - without customer consent. 🙄
Importantly, however, this PR debacle highlights how the IoT is a data farm, which has created "new types of data" that haven't previously been available. 🦄 Pilgrim Beart, founder of IoT management service DevicePilot, points out that "the potential for monetising this data is huge", as "advertisers are always looking for more insights about potential customers and their behaviours". 🕵 But, companies need to be transparent and upfront about any "second side(s) to its business model". ✅
Similarly - writing for the NY Times, John R. Quain, discusses how much data cars "suck up" and where it goes. 🚗 Quain explores the advantages of sharing this data, such as to provide live traffic services. 🚦 However, there is a clear potential "threat to personal privacy and security" if this raw data is made available for purchase. ⛔ If companies are able to "trade and combine information collected from multiple sources" - this poses the risk of re-identification and can provide an extremely detailed insight into individuals' habits. 🔍
Is the digital divide over consumer data widening? ⚖ In light of Sweden's disastrous data breach, the Financial Times provided an excellent overview of the regulatory divergence happening across the globe. 🌍 Interestingly, they conclude with:
The gulf opening up in the way emerging and advanced economies regulate it threatens to erode the competitiveness of companies in the latter. At the same time, in too many emerging economies, states have been slow to entertain the privacy concerns of citizens. To bridge this chasm and head off trouble, it is time to consider a multilateral approach with minimum global standards.
Does ad-tech need data exchange standards? 🤔 Sanjay Agarwal, VP of engineering at Drawbridge, highlights the "strong need" for a "standard format to send data" between data management platforms (DMPs) and demand-side platforms (DSPs) - "resulting in a more seamless exchange of data". ✅ This would enable marketers to "get campaigns set up quicker, more easily receive data back and never have to worry about integration timelines". 🆒
How can smart data be leveraged for business success? 💰 Intriguing white paper by Knowledge@Wharton, in partnership with WNS Global Services, exploring how organisations can "capture smart data" and "conduct analytics to yield the desired insights". 💯 The paper defines "smart data" as "those parts of big data that are relevant for analytics and the resulting refined data sets". 📊 -- This data should help companies determine the "big, fundamental question" of "how valuable will this customer be in the future?". 🛍 In short, this is by:
Organisations must begin with the right philosophical underpinnings in their data strategies, build the data architecture with the requisite democratisation and create an internal culture of sharing and collaboration. Thus prepped for their smart-data journey, they must a) define their problem accurately; b) look for the data that could provide the answers instead of being data-led; c) use new analytics techniques that go beyond conventional regression methods; and d) never swerve away from the empirical, experimentation and theory.
⛓ Neat guide to building the tiniest blockchain.
🍏 Apple launched their first ever technical blog.
💨 Building a wind map with WebGL:
Building a wind map with WebGL, by Vladimir Agafonkin