Difference between revisions of "ANLY482 AY2015-16 Term 2"
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− | '''[https://wiki.smu.edu.sg/ANLY482/AY1516_T2_Group11 Team AYE] | + | '''[https://wiki.smu.edu.sg/ANLY482/AY1516_T2_Group11 Group11-Team AYE]''' |
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* Audrey Lee Zhi Ying | * Audrey Lee Zhi Ying | ||
* Edwin Tan Soon Hong | * Edwin Tan Soon Hong |
Revision as of 16:19, 8 January 2016
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Title | Analytics Practicum Description | Student Member(s) | Project Supervisor | Sponsor |
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To be confirmed | To be confirmed |
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
Analysis of User and Merchant Dropoff for Sugar App | To be confirmed |
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
Group03- Team APSM
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
Group05- Team AP
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
Skyscanner Content Analysis |
The project aims to help with Skyscanner's analyse its content sites in order to facilitate better planning. It will help understand the factors that affect content performance. Deliverables include creating a dashboard with visualizations that will help Skyscanner team to track the performance of articles across weeks and months, matched to trends and seasonality. It will be used to validate some of the intuitions they might have about certain content topics/types and to determine the best time to publish them. The dashboard will benchmark certain metrics against pageviews as well as additional attributes that Skyscanner does not currently analyse via Google Analytics, such as the impact of title, text length, theme of article and number of images. The team will also analyse content pages to determine what differentiates good and bad content based on certain performance metrics. This will be done through Text Mining (Topic Analysis), Content Crawling, MLR and matching with Google Trends API. Data set includes data from Skyscanner websites for the Singapore, Malaysia and Thailand markets. |
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) |
Ms. Antoinette Tan |
To be confirmed | To be confirmed |
Group07- Team YSR
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
Group08- Team AP
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
Group12 Team MYW
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
Group13 Team
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
Marketing Analytics at Tokio Marine | To be confirmed | Group14- Team HEW
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Benito Mable
Vice President, New Opportunities Tokio Marine Asia |
Coming soon... | To provide a client in healthcare industry with descriptive analytics tools for public health monitoring and intervention |
Group15
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Khoo Teck Puat Hospital & SMU T-Lab |
Car Park Overspill Study | To be confirmed |
Group16 Blackbox
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
Social Media Analysis | To be confirmed |
Group17 T(eam)ROLL
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) |
To be confirmed |
To be confirmed | To be confirmed |
Group18
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
Group19
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |
To be confirmed | To be confirmed |
Group20
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | To be confirmed |