Difference between revisions of "ANLY482 AY2016-17 T1 Group2: Project Overview"
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| − | + | <div style="background:#0096da; line-height:0.3em; font-family:sans-serif; font-size:120%; border-left:#bbdefb solid 15px;"><div style="border-left:#fff solid 5px; padding:15px;"><font color="#fff"><strong>Business Problem & Motivation</strong></font></div></div> | |
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| + | As TixCo is the only authorised ticketing service provider for certain events, it is crucial for them to cater to the demand of the mass public. Currently, TixCo is unable to anticipate the demand for the event organised and this post challenge for TixCo to fully capture the demand efficiently. As such, any uncaptured demand is an opportunity lost for TixCo. Hence, it is important for them to understanding the demand for an event. | ||
| − | + | For this, TixCo will need to: | |
| − | + | * Understand the trend and pattern of the number of tickets sold per event | |
| − | + | * Identifying the possible bottleneck for demand | |
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| − | + | <div style="background:#0096da; line-height:0.3em; font-family:sans-serif; font-size:120%; border-left:#bbdefb solid 15px;"><div style="border-left:#fff solid 5px; padding:15px;"><font color="#fff"><strong>Project Objective</strong></font></div></div> | |
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<div style="color:#212121;"> | <div style="color:#212121;"> | ||
| − | + | The objective of this project is to: | |
| + | * Examine the underlying factors that affect the number of tickets sold per event | ||
| + | * Understanding the distribution of the number of tickets sold per event | ||
| + | * Understanding the relationship between the other attributes and the number of tickets sold per event | ||
| + | The project team also aims to develop an appropriate model to predict the number of tickets sold per event, based on the historical data provided by TixCo. | ||
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| − | <div style="background:#0096da; line-height:0.3em; font-family:sans-serif; font-size:120%; border-left:#bbdefb solid 15px;"><div style="border-left:#fff solid 5px; padding:15px;"><font color="#fff"><strong> | + | <div style="background:#0096da; line-height:0.3em; font-family:sans-serif; font-size:120%; border-left:#bbdefb solid 15px;"><div style="border-left:#fff solid 5px; padding:15px;"><font color="#fff"><strong>Datasets</strong></font></div></div> |
<div style="color:#212121;"> | <div style="color:#212121;"> | ||
| − | + | The datasets provided by TixCo are: | |
| + | # Profit & Loss (P&L) records | ||
| + | # Timetables of the events serviced | ||
| + | # Types of events | ||
| + | The data are presented in the form of Microsoft Excel worksheets and contains records over the time span of more than 6 years (Jan 2010 to May 2016). | ||
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Latest revision as of 08:01, 16 October 2016
Business Problem & Motivation
As TixCo is the only authorised ticketing service provider for certain events, it is crucial for them to cater to the demand of the mass public. Currently, TixCo is unable to anticipate the demand for the event organised and this post challenge for TixCo to fully capture the demand efficiently. As such, any uncaptured demand is an opportunity lost for TixCo. Hence, it is important for them to understanding the demand for an event.
For this, TixCo will need to:
- Understand the trend and pattern of the number of tickets sold per event
- Identifying the possible bottleneck for demand
Project Objective
The objective of this project is to:
- Examine the underlying factors that affect the number of tickets sold per event
- Understanding the distribution of the number of tickets sold per event
- Understanding the relationship between the other attributes and the number of tickets sold per event
The project team also aims to develop an appropriate model to predict the number of tickets sold per event, based on the historical data provided by TixCo.
Datasets
The datasets provided by TixCo are:
- Profit & Loss (P&L) records
- Timetables of the events serviced
- Types of events
The data are presented in the form of Microsoft Excel worksheets and contains records over the time span of more than 6 years (Jan 2010 to May 2016).
