Using Threshold Analysis To Discover Emerging Crime Trends In Orlando

Do police departments across the US (the world?) have the bandwidth to pour over crime reports in order to spot trends and mitigate crimes using all the available information?  Given the ever increasing amount of data, now the norm, it will be increasingly difficult to make the best use of this data.  As it applies to Crime, being able to effectively utilize this data should improve the quality of life of everyone.

Crime Dashboard


For week 40, commercial burglaries on sector 2 have increased from an expected count of 7.89 to an actual count of 16.  This is almost 2 1/2 times the expected volume.  (Click image to try analysis or here for image)

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Data Mining Orange County (Orlando Area) Crime

Lets look at recent crime in Orlando and adjacent cities.  What can we find out by exploring Orlando’s crime data?  Is the Central Florida area a relatively safe place?  Can we tell from 90 day’s worth of day?  Are some areas safer than others?  Do we have any false ideas about places in Orlando?

At the very least, lets attempt to get a better understanding of the crime issue which affects us everywhere.

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2014 Miracle Miles 15k Race

Another great, and wet, run!  Non stop rain did not stop the enthusiasm for the thousands of runners the met this year for the 5k and 15k Miracle Miles Event in Orlando.

Highlights for me:

  • First race-in-the-rain!
  • Second race without wearing headphones (in fanny pack as security blanket).  First one was Disney, by choice; more later.
  • Longest race without any walking.
  • (Sub 🙂 ) 9 min/mi.
  • Lots of fun.

I even knew a bunch of runners at event; neat.  Lastly, I feel happy about performance.  First 15k, hence reference for distance, and time-to-beat for next 15k’s , hopeful, PR!



Building on my previous race analysis for the Oviedo 5K, I debated whether to use Tableau (rocks!) again or try Oracle’s Cloud Analytics.

Disclaimer – Happy Oracle Employee.

Even thou it has a 30 day trial, I think free developer accounts will be more suitable to accelerate adoption.  I’ve inquired and await response but they know best I guess.  Oracle does offer such a service for APEX; maybe its a matter of time…

Maybe next time; Tableau to the rescue it is.

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Analyzing the 12th Annual Greater Oviedo 5K with Tableau

I had been meaning to write about this semi recent 5K run in beautiful Oviedo at First Baptist Church.  With by Raul’s insistence, I decided to check this local favorite out.

Held this past May 24th, 2014 on a hot Saturday morning, the course was florida-flat (42 ft elevation gain) but had plenty of shade and had that small-town feeling Oviedo is known for.

With a few weeks to ‘train’ I set out to ramp up the miles in order to reduce my time.  No medals for me yet but I enjoyed the race sights, the crowd and the location.  Nothing like an early short run to set one up for a nice weekend.

For fun, I decided to play around with the results in Tableau and try out the OSX version of the software.  Feature-wise, both Windows and OSX versions are the same, with the Windows version being just a bit more stable with big sets of data.

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Tableau Public Grows Up

Super exiting news today.  Tableau Public’s capabilities have been increased.  This free solution had been limited to 100k records per datasource and to a combined (for all your stuff) size for all your projects to 50Mb.

They have just increased datasources to 1 million records!  Just as impressive, now everyone gets 1 GB of space for their projects.  This is awesome news; it will sure save me lots of time spent scaling down a problem to fit Tableau.  Yay!

Many To Many Relationships in Tableau

While looking for Paul Revere, I recently learned that you can define many-to-many database relationships in Tableau.  I should not have been surprised, Tableau seems to do most things well.  It should wear a cape all the time.

Anyways… before I forget,  here how to to define a many-to-many database relationship in Tableau.

First, lets define the domain for this exercise.  Lets say we have three tables, one for person (PERSON), one for organization (ORG), and an association table defining each persons membership into an organization (ORGPERSON).  Each person can belong to none, one or many organizations and, of course, an organization can have any number of members as well.  

Here is how this would look in a database:


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I Too Found Paul Revere

I am coming from this Reddit post and from here… This post exists solely because I too wanted to find Paul Revere.  I am not even going to use ‘big data’.  Mainly because this data is not big, I do not have a graph database and because I think it would be fun to see what plain old SQL and Tableau can show us.  For truly insightful posts, just visit Kieran Healy, the author of the original post instead.

Kieran makes a very compelling argument on what is possible for surveillance programs the general population may (or not) understand.  His post is really fascinating.  Follow along and you can learn to monitor your citizens as well. 

Heck, I bet you could build your own surveillance network with freely available online services.  Imagine what you could cook up with Google Alerts, Amazon S3, IFTTT and a bit of time!

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Florida Healthcare Costs

If you read any Stephen Few for more than a minute, you’d realize he emphatically stresses clear and simple-looking visualizations.  Well, he does in the one O’Reilly book I have of his where he spends a considerable amount of time pointing out what NOT to do.

With this in mind and looking for an excuse to keep playing with Awesome Tableau Software, I decided to take another look at the Healthcare Costs Data previously talked about at Centers for Medicare and Medicaid Services’.

This time, I restricted the data to the state of Florida (I’m here) and decided to drop the map.  The hopeful intent of this visualization is to provide the needed information as fast as possible.  As before, I cannot embed here but provide the link instead.  Just click on the images to play with visual.



And for perspective, this is what Stephen did.