Data In, Magic Out

The going rate for a magical experience is $63/day. This, as you probably guessed, is the cost of admission for Disneyland. Navigating the park, managing long ride lines, dealing with crowds, and beating the heat can undo an otherwise "magical" trip.

Ridemax to the rescue. The software is amazing. Select the rides and attractions you are interested in and enter this information into Ridemax. Ridemax provides a custom itinerary to offer the best strategy for your Disneyland adventure. The program gives you time of day, wait time, ride time, and walking time to your next attraction. On a trip earlier this year we used it for our itinerary. The results were impressive.

The magic of Ridemax is in the data. Ridemax has massive amounts of historical data allowing the program to provide accurate predictions for the day of the week, dates, time of day, and more. The system also has a sense of distances in order to calculate preferred routes. The end result is a plan that reduces time waiting in lines and the number of footsteps required to reach the next attraction.

The software algorithms used by Ridemax has been adapted to provide software for more accurate wait times for restaurant seating. As storage costs plummet, computing power increases, and historical data expands, data driven modeling solutions will grow rapidly. One solution in particular that will be gaining more attention is traffic advise. The population growth in the US will tax our road and highway infrastructure system and further the traffic congestion in our cities. More consumers will be using software for optimum routes and departure times for their commutes in turn. With Google's impressive mapping technologies, it would be a natural progression for Google to provide driving directions that take into account historical traffic patterns based on time, date, day, and weather conditions. When that data is linked to our GPS-enabled phones and helps cut our commute times significantly, that will truly be magic.