ISSS608 2016-17 T1 Assign3 Mukund Krishna Ravi Approach
APPROACH
With the movement and communication data which have been given to me i will first evaluate the communication data to arrive at insights
Dataset
The dataset used comprised the following for the period of 6 to 8 Jun 2014 (Friday to Sunday):
- Movement data: this covered the movement and check-in records for users of the app devices. The volume of movement data for all 3 days totaled 26,021,963 rows.
- In-app communication data: this covered communications between paying park visitors and communications between visitors and park services, and records of text sent by users to external parties. The volume of communication data for all 3 days totaled 4,153,329 rows.
Data Processing Required
For the data processing of the communications data, i first split the data and time of each of the date-time field over all the 3 days. I converted all the dates on a 12 hour format to a 24 hour format.
All the dates were rolled up and a unique count of each was obtained. This will be used to visualize the spike in the communications data. Each of these date points would be plotted on the X axis and the unique ID counts which signify the number of calls made/min. This would be visualized as a time series to observe the changes in communication pattern.
Using JMP and Tableau to process communications data
To understand the communication data we first plot the rolled time against the number of instances of rolled time values. From this visualization we obtain many insights on Gephi. For instance the Gephi tool will be used only in the time zone where there is a spike in the data. This roll up operation is performed across all the days i.e. Friday, Saturday and Sunday.
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