Fits and Starts

I have a few shade tree, or hobby projects I have been thinking about. But that’s mostly been what I have been doing, thinking about it.

So to put some structure and possible progress around these ideas, I have been creating some GitHub reposotories.

These projects are one part learning exercise, one part sharing, and maybe even some community building.

Here is a run down on a few project and ideas:

Vessel Traffic

Every summer our family spends a long weekend in Mackinaw City, MI with some of my cousins, and other hangers-on. One of those hangers-on is a former crew member of a Great Lakes freighter. A favorite pastime is watching and indentifying these freighters (trainspotting style)  pass through the Straits of Mackinac

My Vessel Traffic repository is dedicated to applying my interests in GIS and Busines Intelligence to this pastime.

Data Dot Gov

Similar to Vessel Traffic, the DataDotGov project is a catchall of Business Intelligence data derived from the Data.Gov web site.

See Kendra Little’s blog post Free, Open License Dataset at Data.gov for more information.

CensusDw

CensusDw is like the DataDotGov but dedicated to Business Intelligence insight gained with US Censis data.

Happy coding.

Posted in Business Intelligence, Data Integration, Database BI, Open Source | Leave a comment

SQL Server naming conventions

Starting a new project in 2015. I am putting some personal/hobby projects on GitHub. My aim is to share projects, documents, and other resources. I am hoping it be useful, and possibly find some co-conspirators.

The first item is a collection software development style guides. Here I’ll gather some resources and (wait for it) best practices. I thought of just collecting them in my own private storage, but I am in a sharing mood at this time.

First document out of box is a document outlining some SQL Server naming conventions.

Happy coding.

Posted in Open Source, SQL, Uncategorized | Tagged , , | Leave a comment

Riding the quantified self wave.

The past couple of months I have heard much about the quantified self from a number of different sources. As a data person this got my attention first as a curiosity, and then as a potential convert. The tipping point was Scott Hanselman’s podcast with Chris Dancy, the world’s most quantified man.

The promise I am focused on is that merely collecting data will lead one to better and more informed decisions. Or as Radiohead put it: fitter, happier, more productive, comfortable, not drinking too much.

Past attempts to journal, or otherwise document my life have failed due to lack of consistent data entry. Today’s app world now has dozens of services that passively collect data on where you go, and what you do. OK, sounds a little NSA creepy. But the tradeoff is passively collected data. I go to the gym, and later I see it’s been recorded for me.

Another cool thing, especially for a data geek such as myself, is most of these services make the data available to the user, usually as a CSV download. So not only can I use built in data analysis tools, I can download, load, and combine with my own local data.

Here are a few of the app I am using to get started:

  • Chronos
    • Very detailed
    • iPhone app keeps track of movements for passive data collection
  • Foursquare
    • No introduction needed here.
  • Myfitnesspal
    • Manual data entry required
    • Very detailed tracking for diet and fitness goals
  • IFTTT (It this then that)
    • GUI driven data integration with a boat load of popular services
  • AskMeEvery
    • Simple interface for tracking measurable data (i.e. what’s my weight?)
    • Integration with email and text messaging
Posted in Data Integration, Database BI, Quantified Life, Social Networking | Leave a comment