IS480 Team wiki: 2012T1 6-bit PD Business Intelligence and Analytics
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CodeIgniter has a Benchmarking class that is always active, enabling the time difference between any two marked points to be calculated. In addition, the benchmark is always started the moment the framework is invoked, and ended by the output class right before sending the final view to the browser, enabling a very accurate timing of the entire system execution to be shown.
Chapalang Benchmark is a custom tool developed with the foundation of CodeIgniter’s Benchmarking class. Additional customization has been made to reflect extended measurement of execution for process-based series of activities, integrated with a database table to support other analytical execution.
One of the purpose of Chapalang Benchmark is to support an audit trail on the activities performed by users on Chapalang!. The tool collects the following set of data:
- Member ID
- Controller method
- Start timestamp
- End timestamp
- Elapsed time
By having Chapalang Benchmark to support an audit trail, we are able to trace the series of activities performed by a specific user on our system, given any time period.
While it may not be friendly to the privacy of users, and not efficient to design models customized to a specific user, it is useful to use the activity data collected to support advance analytics. At this stage, the data acts as a complementary operational data source for our analytics behind the Personalized Dashboard.
There are other usefulness of the activity data to discover system anomalies, user experiences, and more. Some examples are further elaborated below.
The purpose of Chapalang Analytics is primarily to support the low-level function, Personalized Dashboard of the portal. While that is the only application of Chapalang Analytics at this stage, it can be further expanded into other data-driven and user-oriented features which include but not limited to, target advertising and content filtering.
Operational Data Source
The analytics will make use of the following data:
- Facebook statuses, likes, post times, friends, gender, birthday, relationship status
- Chapalang Benchmark, which collects data on all user activities on Chapalang!, such as browsing history and past purchases
- Sentimental database, containing a list of words that characterises user’s personality and behaviour
The analytics will make use of the following techniques:
- Semantic Analytics
- Sentimental Analytics
- Rule-based Analytics
Analysis of User’s Facebook Persona
The first analytical step of Chapalang Analytics is to analyse a user’s Facebook persona. Through the analysis of the user-specific ODS, we will identify certain characteristics of a user.