Does your company view data privacy as a tier-1 consideration? What can data visualisation learn from punks? How does data go dark? Did you (your kids) make it on Santa's Nice List? How much self- indulgence do Millennials need to give up to get on the property ladder? What could a tech-enabled Christmas look like in 2026?
Can Trump's government get its hands on Silicon Valley's big data? Brian Feldman points out that even though most of the tech giants have released statements against Trump's so-called "Muslim database", this data can be collected by big-data analysis companies instead. In particular by Palantir - which is backed by tech billionaire and Trump transition advisor Peter Thiel. 😧
-> EXTREMELY WORRYING redacted documents have emerged which show how Palantir have been supporting the US Customs and Border Protection agency (CBP) to track and assess immigrants. 😱 The system, the Analytical Framework for Intelligence (AFI), would provide Trump with the profiling algorithms and framework necessary to implement "extreme vetting". 😶
Reportedly ONE BILLION Yahoo's users personal data has been sold on the dark web. Alongside names, passwords and phone numbers, this personal data also includes backup email addresses (which potentially have the same password) and unencrypted security questions and answers - providing the purchaser with everything needed to unlock an account. 🤐
Kristina Bergman emphasises the importance of prioritising data privacy - as it could make or break the sale of your company. Data privacy is now a TIER-1 CONSIDERATION for investors, lawyers and startup founders - and if not dealt with diligently, it can "severely devalue or company or potentially even kill an M&A transaction entirely". Wonder what will happen to Yahoo now...🙃 - Data privacy laws are due to become extremely stringent, and data breaches EXPENSIVE, in May 2018 when GDPR legislation comes into action. 🤓
Andy Cotgreave discusses what data visualisation can learn from punks, by embracing messy visual exploration to improve skills and make new discoveries. 🤘 This has been seen throughout 2016 in #MakeoverMonday - a weekly data vis project which gets users to rework a chart and data to "retell the story more effectively, or find a new story in the data". 👍