The truth at any cost lowers all other costs — curated by former US spy Robert David Steele.
(Big) Data Burping Data integration from an old system to a new system is coded for trouble. The system swallowing the data is guaranteed to have indigestion and the only way to relieve the problem is by burping. Chez Brochez has dealt with his own share of data integration issues and in his article, “Tips …
A Google Savior for US Government Web Sites Quote to Note: Big Data Getting Even Biggerest Super Fastly Full text with Phi Beta Iota comments and additional links below the fold.
Microsoft Puts Machine Learning in the Cloud Machine learning is ascending to the cloud. The Register asks, “Do Data Centers Dream of Electric Sheep? Microsoft Announces Machine Learning Cloud.” As competition in the world of SaaS and remote hosting continues to escalate, this move may set Microsoft ahead of Amazon and Google (for now). Our …
Big Data Stress at Both Ends of the Lens An interesting article at the New Inquiry looks at the psychological effects of both surveying and being surveyed in the modern, data-driven world. It’s an interesting read, and I urge the curious to check out the whole piece. Writer Kate Crawford begins with ways intelligence agencies …
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Rising Startup Tamr Has Big Plans for Data Cleanup An article Gigaom is titled Michael Stonebraker’s New Startup, Tamr, Wants to Help Get Messy Data in Shape. With the help ($16 million) from Google Ventures and New Enterprise Associates, Stonebraker and partner Andy Palmer are working to crack the ongoing problem of data transformation and …
Kevjn Lim is an independent writer and Middle East foreign policy analyst at Open Briefing: The Civil Society Intelligence Agency. In the latter half of 2013, he was Turkey representative for the Syria Needs Analysis Project (SNAP), covering the Syrian crisis in the northern governorates and Turkey. From 2007-2011, he served as delegate with the International Committee of the Red Cross (ICRC) in …
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20 short tutorials all data scientists should read (and practice) Vincent Granville DataScienceCentral, 15 February 2014 We are now at 20, up from 17. I hope I find the time to write a one-page survival guide for UNIX, Python and Perl. Here’s one for R. The links to core data science concepts are below – I …
