Difference between revisions of "AY1617 T5 Team AP Methodology"
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| + | ==<font face ="Impact" color= #00ADEF size="5" >Discovery(Leading Business Domain)</font>== | ||
| + | Our team aim to understand SGAG through exploring the content published by SGAG through multiple channels, namely SGAG’s social network services, website and media contents. <br/> | ||
| + | ==<font face ="Impact" color= #00ADEF size="5" >Discovery(Business Problem Discovery)</font>== | ||
| + | Through interviews and speaking with the founder of the company, our team aims to understand the business problems of SGAG to assist us in identifying problems and translating them into analytics objective. <br/> | ||
| + | ==<font face ="Impact" color= #00ADEF size="5" >Data Preparation(Data Collection)</font>== | ||
| + | SGAG will be able to provide us with data of the uploaded video posts, generated from their facebook and youtube pages with variables listed above. Apart from what is given, we would also like to gather additional information of the videos, including the comments on the videos, characters involved in the video, video resolution, as well as the video type, whether it is an original or reposted video. As SGAG uploads videos of various categories and resolutions (Filmed using a phone versus video camera), we would like to accurately categorise them to further increase the dimension of the data set. <br/> | ||
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| + | ==<font face ="Impact" color= #00ADEF size="5" >Data Preparation(Data Preparation)</font>== | ||
| + | Some of the datasets provided are not structured in the format suitable for analysis to be done (ie: Additional derived columns need to be added, tables need to be traversed etc.). | ||
| + | <br/> | ||
| + | Data required for analysis on the video specifications in relation to audience receptivity will require additional use of open source tools like EXIFTool to extract the EXIF (Camera data) data like video width and video height. <br/> | ||
Revision as of 02:08, 1 January 2017
Contents
Discovery(Leading Business Domain)
Our team aim to understand SGAG through exploring the content published by SGAG through multiple channels, namely SGAG’s social network services, website and media contents.
Discovery(Business Problem Discovery)
Through interviews and speaking with the founder of the company, our team aims to understand the business problems of SGAG to assist us in identifying problems and translating them into analytics objective.
Data Preparation(Data Collection)
SGAG will be able to provide us with data of the uploaded video posts, generated from their facebook and youtube pages with variables listed above. Apart from what is given, we would also like to gather additional information of the videos, including the comments on the videos, characters involved in the video, video resolution, as well as the video type, whether it is an original or reposted video. As SGAG uploads videos of various categories and resolutions (Filmed using a phone versus video camera), we would like to accurately categorise them to further increase the dimension of the data set.
Data Preparation(Data Preparation)
Some of the datasets provided are not structured in the format suitable for analysis to be done (ie: Additional derived columns need to be added, tables need to be traversed etc.).
Data required for analysis on the video specifications in relation to audience receptivity will require additional use of open source tools like EXIFTool to extract the EXIF (Camera data) data like video width and video height.
