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.
Microsoft Viva
Microsoft Viva is an employee experience platform that brings together communications, knowledge, learning, resources, and insights in the flow of work. Powered by Microsoft 365 and experienced through Microsoft Teams, Viva fosters a culture that empowers people and teams to be their best from anywhere.
Viva Learning
Viva Insights
Viva Topics
Viva Connections
https://www.thinkdataanalysis.com/microsoft_viva.html
Five Steps to Simplify Data Marts and BI Solutions
Microsoft recently shared what I think is a pretty useful whitepaper on how to approach Data Marts and BI Solutions.
https://thinkdataanalysis.blob.core.windows.net/files/FiveStepsSimplifyDataMartandBISolutions.pdf
Modern Analytics Architecture
Microsoft provides valuable documentation on how it sees the Modern Analytics Architecture evolving. More information can be found at the link below:
Modern analytics architecture with Azure Databricks – Azure Solution Ideas | Microsoft Docs
Think Data Analysis.com
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.
15 Years since Hans Rosling first excited the world!
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! 🙂
Avengers Power BI
Click here for a Power BI App about the Avenger’s movies!
Note: If you are prompted for credentials send me an email!
Nathan Yau’s Reading List
I follow and really like Nathan Yau. His site FlowingData.com is a great resource for Data Visualization inspiration. Below is his reading list for during the crisis:
Making Charts
Books specifically about making and using charts…
- Info We Trust by RJ Andrews — Unique because Andrews hand-drew all of the examples himself.
- Data Visualisation by Andy Kirk — It’s next up with the Datavis Book Club.
- Designer’s Guide to Creating Charts and Diagrams by Nigel Holmes — I bought a used copy a while back for a couple of dollars. I’ve always admired Holmes’ style.
- Wordless Diagrams by Nigel Holmes — Got this one too, pretty much for the price of shipping.
- Elevate the Debate edited by Jonathan A. Schwabish — A practical guide aimed at communicating technical research to a wider audience.
Statistics
Making sense of numbers…
- Factfulness by Hans Rosling — I’ve heard many good things. Probably first up in my queue.
- Exploratory Data Analysis by John Tukey — It’s an outdated textbook but it’s historically rich. I’ve never read it cover-to-cover.
- How Charts Lie by Alberto Cairo — So important these days.
- Understanding data and statistics in the medical literature by Jeffrey Leek, Lucy D’Agostino McGowan, and Elizabeth Matsui
Development
Some code…
- R Packages by Hadley Wickham — I know the basics, but I should know more.
- The Book of R by Tilman M. Davies — A big, fat reference.
- Some visualization with Python book. I’ve seen some books, but is there a well-regarded reference?
Design
Outside visualization, but applicable…
- The Shape of Design by Frank Chimero — Got this years and years ago. I will assume it has aged like a fine wine.
- The Design of Everyday Things by Don Norman — Charts are everyday things.
- Emotional Design: Why We Love (or Hate) Everyday Things by Don Norman
- Understanding Comics by Sott McCloud — Telling stories visually. Sounds familiar.
Inspiration
To think about various visual forms…
- History of Information Graphics by Sandra Rendgen and Julius Wiedemann — This is a giant book with giant pictures.
- All Over the Map by Betsy Mason and Greg Miller — The stories behind the visuals always make the picture more interesting.
- How To: Absurd Scientific Advice for Common Real-World Problems by Randall Munroe — I admire Munroe’s ability to explain things with stick figures and clear diagrams.
- Math With Bad Drawings by Ben Orlin — Again, interested in the process more than I am in the material.
Dashboard Comparison
A took a quick look at the COVID-19 data using Power BI and Qlik Sense. Both have their advantages – but are using the same dataset. A shared table in Snowflake (CT_US_COVID_TESTS).
Coronavirus-19
This is a difficult time for many of us. My thoughts are first with all of the people suffering from the disease and it’s impact. Also with the heroic first responders, the men and women who are risking their own lives to save others.
There are a number of interesting site I’ve been following to get more info. The site below does a great job of explaining the growth of the virus and how to tell if we are flatting the curve.
The original Johns Hopkins site uses a map delivered by ESRI and ArcGIS to track the progression of the virus:
https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6
