For the last 20 years, ESRI has been capturing geographic and demographic data. In the 90’s Acxiom (and others) came up with Lifestyle Segmentation. ESRI started in 1969 and today maps “everything” down to the household level.
I’m surprised by the accuracy of Tapestry Segmentation. The top three segments in my zip code are: “Top Tier”, “Comfortable Empty Nesters” and “In Style”. Pretty accurate – with one data point. I’m an Empty Nester who would like to be “In Style” or “Top Tier” but feel very lucky and fortunate to be “comfortable”.
Differential privacy seeks to protect individual data values by adding statistical “noise” to the analysis process. The math involved in adding the noise is complex, but the principle is fairly intuitive – the noise ensures that data aggregations stay statistically consistent with the actual data values allowing for some random variation, but make it impossible to work out the individual values from the aggregated data. In addition, the noise is different for each analysis, so the results are non-deterministic – in other words, two analyses that perform the same aggregation may produce slightly different results.
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Recently I decided to move from AWS to Azure for the hosting of my “Sandbox” sites. With the move, I plan to add serve up live interactive data content highlighting different “data” projects of personal and professional interest.
Much of what I’ve worked on is contained on “corporate” portals and intranets. The move to Azure from AWS for “server based” content will allow more flexibility and access to Power BI, SharePoint and Microsoft Teams.
I had a chance to take a look today at Tableau Public. I’ve used it in the past but to be honest Tableau is my third favorite visualization tool (behind Qlik and Power BI). I was impressed to see they used an example mimicking the famous TED talk by Hans Rosling. If you haven’t seen this and you’re interested in data and analytics – its a must watch! 🙂