Difference between revisions of "ANLY482 AY2017-18T2 Group14 Project Overview"
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<div style="background: #EAEAEA; padding: 10px; font-weight: bold; text-align:center; line-height: wrap_content; text-indent: 20px;font-size:20px; font-family:helvetica"><font color= #3d3d3d>Motivation</font></div> | <div style="background: #EAEAEA; padding: 10px; font-weight: bold; text-align:center; line-height: wrap_content; text-indent: 20px;font-size:20px; font-family:helvetica"><font color= #3d3d3d>Motivation</font></div> | ||
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− | Our project is largely focusing on helping the project sponsor | + | Our project is largely focusing on helping the project sponsor improve analytical process on the large On-demand Delivery data (ODD). The legacy system of data analysis in the company is still using manual data collection and calculations through Microsoft Excel. It takes resources and time for analysts to do analysis. To improve the low efficient analytical process, we are expected to use Power BI to connect database directly and generate report using filters and query languages. By doing so, the company’s analysts would be able to generate report in a short period of time. Furthermore, our team also aims to familiarize ourselves with handling real business data, apply what we have learnt into practice and enhance our analytical skills via hands-on. |
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Revision as of 16:16, 12 April 2018
Our client is one of the global market leader in the logistics industry. It provides domestic and international mail and parcel services to its customers by leveraging on their well-built expertise in international parcel, express, air and ocean freight, road and rail transportation.
However, they are still facing problems with their customers in delivery service. Parcels are not usually sent on time agreed with the customer, this causes customer dissatisfaction and costs them additional resources as a result ranging from having to re-performing another delivery or possible lost business. Even performing re-deliveries causes our client unnecessary costs such as time, labour, petrol which could be avoided.
Our research efforts are mainly involved by the need to discover potential problems caused by data inconsistencies, how it affects data operations and the decisions made due to analytical results from these data. The aim of this research is to provide organisations and businesses methods and tools that they can help to reduce or even eliminate the undesirable effects from these inconsistencies and use data to make better decisions.
Specifically, it aims to address these issues:
- Standardizing and cleaning of data from various sources and storage formats
- Migration of Data from File-based sources into a Database Management Systems
- Improving Database Performances
- Report Generation
- Discover Operational insights from data
All these will better allow our client to make better and much informed decisions regarding their services to provide their customers better service.
Our project is largely focusing on helping the project sponsor improve analytical process on the large On-demand Delivery data (ODD). The legacy system of data analysis in the company is still using manual data collection and calculations through Microsoft Excel. It takes resources and time for analysts to do analysis. To improve the low efficient analytical process, we are expected to use Power BI to connect database directly and generate report using filters and query languages. By doing so, the company’s analysts would be able to generate report in a short period of time. Furthermore, our team also aims to familiarize ourselves with handling real business data, apply what we have learnt into practice and enhance our analytical skills via hands-on.
In this project, we will adopt visualization techniques and tools to:
- Integrate existing data sets of different formatting into a unified data format
- Establish an automatic dashboard that allows data exploration and visualization and adds value to their daily operation
- Discover meaningful insights from given data