Hackers and Slackers

Google Cloud Platform: Creating an Instance and Configuring DNS

Quality of services over quantity

For the last few weeks I've been enamored with Google's cloud platform, aptly named Google Cloud Platform. GCP contains the things you might expect from a young player in the 'screw AWS' space: much of what exists on AWS has an equivalent on GPC, but certain subtleties exist, such as the lack of Python serverless functions and so forth. That said, GCP makes up for any shortcomings by leveraging services exclusive to Google.

In my opinion, GCP is the first

Google Cloud Author imageTodd Birchard July 14
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Your Invitation to the Pivot Party

Adventures in Excel

I know its been a while, but you'd be surprised how little time an energy you have when you're building a plane while you're flying it...or perhaps, if you've been reading along with this series, you won't.

Before jumping right into the deep end and showing you some lesser known (but supremely useful) tricks to save even more time (which you'll no doubt use to implement new tricks to save more time, it's a vicious cycle), allow me to

Excel Author imageMax Mileaf July 21
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Data Could Save Humanity, if it Weren't for Humanity

Just another case for robot overlords

A decade has passed since I entered the realm of data-centric technology engineering and management. As time pushed forward and our tools evolve with our attitudes, cultural mind shift amongst businesses begin to build a clear yet slowly-growing narrative.  Unfortunately, I can't say that much about that shift has been positive.

While we might all agree that 'data addiction' is at an all-time high, there's a good chance none of us fully know what we mean by that. We may

Data Author imageTodd Birchard July 20
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Lynx Roundup, July 17th

Scaling a Graph db, presenting survey data, badly presenting data

https://neo4j.com/blog/scale-out-neo4j-using-apache-mesos-and-dc-os/

https://www.r-bloggers.com/presenting-survey-data/

Quantifying stuff has a reputation for creating absurdities.  Some would say that other methods create an equal number of absurdities, except they're just way harder to see.  http://andrewgelman.com/2018/07/03/flaws-stupid-horrible-algorithm-revealed-made-numerical-predictions/

https://flowingdata.com/2018/06/28/why-people-make-bad-charts-and-what-to-do-when-it-happens/

https://github.com/solid/solid

Statistics Author imageMatthew Alhonte July 17
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A Dirty Way of Cleaning Data (ft. Pandas & SQL)

Code Snippet Corner ft. Pandas & SQL

Warning The following is FANTASTICALLY not-secure.  Do not put this in a script that's going to be running unsupervised.  This is for interactive sessions where you're prototyping the data cleaning methods that you're going to use, and/or just manually entering stuff.  Especially if there's any chance there could be something malicious hiding in the data to be uploaded.  We're going to be executing formatted strings of SQL unsanitized code.  Also, this will lead to LOTS of silent failures, which

Pandas Author imageMatthew Alhonte July 16
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