Will companies be able to convince consumers to still hand over their personal data when GDPR comes into action? Gmail user? Are you taking part in the Data Science Bowl? Should developers consider themselves specialists or generalists? Could you be a citizen data scientist? Have you lost control of your digital presence?
Does data have an image problem? Negative news naturally receives the most press coverage as it shocks and engages the reader. However, as discussed by Guy Marson, this means that the majority of "data" stories in the press are "on a hack, data leak or misuse of data". This warps consumer view to mis-trusting companies over how their personal data is used and stored. 🙄
-- For example - 2016 was a record year for data breaches. Headlines like this do not fill consumers with confidence or reflect how data is actually helping consumers. GDPR will make it compulsory to "explain to consumers how and why their data is being used" - so companies need to be able to convince consumers that it in their best interest to hand over their personal information. 😬
Gmail user? Don't fall victim to this dangerously convincing phishing attack. The fake login page contains the accounts.google.com subdomain - but uses a "data URL" to "include a complete file in the browser location bar" which is actually a "very long string of text". If you haven't already, enable two-factor authentication... 📧
This year's Data Science Bowl has kicked off 🏈📈 - the world's premier data science for social good competition. This year's challenge is to turn machine intelligence against lung cancer. Get involved here. 🙌
Specialist or generalist? Itamar Turner-Trauring discusses which path is better for software developer's career. ⚖ Context is everything - in short, be a generalist but market yourself as a specialist if applying for a specific job role.
According to Gartner, more than 40% of data science tasks will be automated by 2020. 🤔 This will further the growth of "citizen data scientists" -- employees whose primary job is non-stats/ analytics, but can create "models that use advanced diagnostic analytics or predictive and prescriptive capabilities". 💪
Vector models in machine learning, by Erik Bernhardsson
DataSift has teamed up with LinkedIn to "build up more data about how LinkedIn is used and what is talked about on there". This will provide deeper insights into how LinkedIn is used, which will in turn help marketers maximise their advertisements. Check out this write up by Ingrid Lunden. ✅