Difference between revisions of "ANLY482 AY2017-18T2 Group27 : Project Overview / Methodology"
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Since we have not obtained the data yet, we were unable to come up with a comprehensive project methodology. | Since we have not obtained the data yet, we were unable to come up with a comprehensive project methodology. | ||
| − | Our brief plan of action includes doing descriptive analytics and predictive analytics. Descriptive analytics will be done via doing data visualisation. We will be combining various descriptive analysis of operational factors into a dashboard which will allow | + | Our brief plan of action includes doing descriptive analytics and predictive analytics. Descriptive analytics will be done via doing data visualisation. We will be combining various descriptive analysis of operational factors into a dashboard which will allow Company X to monitor, track and diagnose. Additionally, a regression model to allow Company X to better forecast shipment behaviour. We will also be doing secondary research from various journal articles to potentially supplement our project. |
As of now, we will be focusing on understanding and cleaning the data. | As of now, we will be focusing on understanding and cleaning the data. | ||
</div> | </div> | ||
Revision as of 00:40, 2 March 2018
| Description | Data | Methodology |
7.0 Methodology
7.1 Tools Used
In this project, 2 main tools will be used - Power BI and Python.
Power BI is the choice of tool by DHL and data visualisation will be done on this medium. Also, with the large dataset, Python will be used to build regression model.
7.2 Project Methodology
Since we have not obtained the data yet, we were unable to come up with a comprehensive project methodology.
Our brief plan of action includes doing descriptive analytics and predictive analytics. Descriptive analytics will be done via doing data visualisation. We will be combining various descriptive analysis of operational factors into a dashboard which will allow Company X to monitor, track and diagnose. Additionally, a regression model to allow Company X to better forecast shipment behaviour. We will also be doing secondary research from various journal articles to potentially supplement our project.
As of now, we will be focusing on understanding and cleaning the data.
