Difference between revisions of "ANLY482 AY2017-18T2 Group07"
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Note: due to the confidential nature of this project, we shall refer to our Project Sponsor as the "Sponsor" throughout this wiki. We will not be able to publish major findings and any visualization or graphics made in line with this measure.
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<font color="#212121" face= "Franklin Gothic Book" size=4px> | <font color="#212121" face= "Franklin Gothic Book" size=4px> | ||
| − | Our sponsor company is one of the worlds largest logistics companies providing international courier, parcel and express mail services | + | Our sponsor company is one of the worlds largest logistics companies providing international courier, parcel and express mail services. |
| − | Our sponsor | + | Our sponsor is the consulting arm of this logistics company. It aims to improve operational efficiency across multiple business accounts to ensure that the Group Account Managers (GAM) are successfully able to increase value across their stakeholders. |
</font> | </font> | ||
</p> | </p> | ||
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<p> | <p> | ||
<font color="#212121" face= "Franklin Gothic Book" size=4px> | <font color="#212121" face= "Franklin Gothic Book" size=4px> | ||
| − | Our team | + | Our team aims to help the GAMs make better sense of their data. During this preliminary stage, we achieved the following:<ol> |
| − | <ol> | + | <li>Flagged Inconsistent Entries - |
| − | <li> | ||
<ul> | <ul> | ||
| − | <li> | + | <li>Identified inconsistencies in the data, for example- a text input in a numeric column</li> |
| − | <li> | + | <li>Identified missing values in the data</li> |
</ul> | </ul> | ||
</li> | </li> | ||
| − | <li> | + | <li>Explored the data - |
<ul> | <ul> | ||
<li>Basic exploratory analysis to check skews in the data and identify general trends</li> | <li>Basic exploratory analysis to check skews in the data and identify general trends</li> | ||
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</li> | </li> | ||
</ol> | </ol> | ||
| − | |||
</font> | </font> | ||
</p> | </p> | ||
Revision as of 00:05, 26 February 2018
Team Data Heavy Legends(DHL) wants to help its sponsor provide its service in the most efficient manner possible by making sense of the data they currently have. Through our efforts we hope to satisfy all stakeholders involved equally.
Project Sponsor
Our sponsor company is one of the worlds largest logistics companies providing international courier, parcel and express mail services. Our sponsor is the consulting arm of this logistics company. It aims to improve operational efficiency across multiple business accounts to ensure that the Group Account Managers (GAM) are successfully able to increase value across their stakeholders.
Objectives
Our team aims to help the GAMs make better sense of their data. During this preliminary stage, we achieved the following:
- Flagged Inconsistent Entries -
- Identified inconsistencies in the data, for example- a text input in a numeric column
- Identified missing values in the data
- Explored the data -
- Basic exploratory analysis to check skews in the data and identify general trends
- Identify the bottlenecks in the shipment journey affecting the operational performance
- Analyze the shipment patterns and trends for lane-wise pairs in the existing dataset
