Difference between revisions of "ANLY482 AY2017-18 T2 Group 15"

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| style="padding:0.4em;  font-size:100%;  text-align:center; background-color:#333399; font-family:Century Gothic; " width="15%" | [[ANLY482 AY2017-18T2 Group 15|<font color="#ffffff" size=4><b>Home</b></font>]]
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| style="padding:0.4em; font-size:100%; background-color:#000999;   font-family:Century Gothic;   text-align:center; color:#E6E87D" width="22%" |[[ANLY482 AY2017-18T2 Group15 Project Overview|<font color="#ffffff" size=4><b>Project Overview</b></font>]]
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[[ANLY482_AY2017-18_T2_Group 15 |<font face ="Helvetica" color="#3f3d3d"><strong>HOME</strong></font>]]  
  
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| style="padding:0.3em; font-family:Arimo; font-size:110%; border-bottom:4px solid #aaaaaa; border-top:4px solid #aaaaaa; background:#ffcc16; text-align:center;" width="10%" |
| style="padding:0.4em; font-size:90%; background-color:#000999; font-family:Century Gothic; text-align:center; color:#E6E87D" width="23%" |[[ANLY482 AY2017-18T2 Group15 Data Analysis|<font color="#ffffff" size=4><b>Data Analysis</b></font>]]
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[[ANLY482_AY2017-18_T2_Group15_Project_Overview|<font face ="Helvetica" color="#3f3d3d"><strong> PROJECT OVERVIEW</strong></font>]]
  
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| style="padding:0.3em; font-family:Arimo; font-size:110%; border-bottom:4px solid #aaaaaa; border-top:4px solid #aaaaaa; background:#ffcc16; text-align:center;" width="10%" |
| style="padding:0.4em; font-size:100%; background-color:#000999; font-family:Century Gothic; text-align:center; color:#E6E87D" width="20%" |[[ANLY482 AY2017-18T2 Group15 Documentation|<font color="#ffffff" size=4><b>Documentation</b></font>]]
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[[ANLY482_AY2017-18_T2_Group15_Data_Analysis|<font face ="Helvetica" color="#3f3d3d"><strong> DATA ANALYSIS</strong></font>]]
  
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| style="padding:0.4em; font-size:90%; background-color:#000999;  font-family:Century Gothic; text-align:center; color:#E6E87D" width="20%" |[[ANLY482 AY2017-18T2 Group15 Analytics Reflection|<font color="#ffffff" size=4><b>Reflection</b></font>]]
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[[ANLY482_AY2017-18_T2_Group15_Documentation|<font  face ="Helvetica" color="#3f3d3d"><strong> DOCUMENTATION</strong></font>]]
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[[ANLY482_AY2017-18_T2_Group15_Recommendations|<font  face ="Helvetica" color="#3f3d3d"><strong> RECOMMENDATIONS</strong></font>]]
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[[ANLY482_AY2017-18_T2_Group15_About_group|<font face ="Helvetica" color="#3f3d3d"><strong>ABOUT US </strong></font>]]
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[[ANLY482_AY2017-18_Term_2|<font  face ="Helvetica" color="#3f3d3d"><strong>BACK TO MAIN ANLY82 </strong></font>]]
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| style="vertical-align:top;width:50%;" | <div style="padding: 1px; text-align:center; line-height: wrap_content; font-size:14px; border-top:3px solid #ffcc16;border-bottom:3px solid #ffcc16 "> [[ANLY482 AY2017-18 T2 Group15 Home Version 1| <font color="#000000"><b>'''VERSION 1'''</b>]]
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| style="vertical-align:top;width:50%;" | <div style="padding: 1px; text-align:center; line-height: wrap_content; font-size:14px;  border-top:3px solid #ffcc16;background:#545454;border-bottom:3px solid #ffcc16"> [[ANLY482_AY2017-18_T2_Group 15 | <font color="#FFFFFF"><b>FINAL</b>]]
  
 
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<div style="background: #ffebba; padding: 12px;font-family:Helvetica; font-size: 15px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #ffcc16 solid 10px; border-right: #ffcc16 solid 10px; text-align:center "><font color="#3f3d3d">PROJECT DESCRIPTION</font></div>
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::Data visualization software is a powerful analytical tool. With the necessary data, an ideal set of visualizations provides clear information about sales trends and operational data and is highly adaptable to users’ changing needs. This helps businesses better understand their strengths, weaknesses, and performance against competitors, and make quicker and more effective business decisions. A competitive edge is thus obtained against users of primitive data visualization methods, such as static charts and graphs - which are less customizable, take more time to update and provide less information in the long run.
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::This project will explore the benefits of data visualization improvements on a client, which is a well-established Fast-Moving Consumer Goods (FMCG) company. The study will use actual data for distribution, sales, Key Performance Indicators (KPIs) and price between 2014 and 2017. The data is currently visualized in a simple Excel dashboard, which provides limited information. In this project, we begin with data-cleaning and transformation processes in converting raw data into the flat data structure necessary for visualization, then assess the suitability of two more powerful and sophisticated visualization methods – Tableau and Qlik Sense. Finally, we recommend the platform which best suits the client’s needs, along with plans and recommendations for the client moving forward.
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::As a project team, we aim to improve our client’s data processing and analytics methods to improve their efficiency, provide clearer and more dynamic visualizations, and allow them to make improved marketing decisions.
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<div align="center">
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<div style="background: #ffebba; padding: 12px; font-family:Helvetica; font-size: 15px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #ffcc16 solid 10px; border-right: #ffcc16 solid 10px;  text-align:center "><font color="#3f3d3d">PROJECT STATUS</font></div>
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<div style="background: #000054; padding: 0px; font-weight: bold; text-align:center; line-height: wrap_content; text-indent: 20px;font-size:20px; font-family:Century Gothic"><font color= #ffffff>Deliverables</font></div>
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[[File:Group15timeline.PNG|700px|center]]
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<div align="centre">
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<div style="background: #ffebba; padding: 12px; font-family:Helvetica; font-size: 15px; font-weight: bold; line-height: 1em; text-indent: 15px; border-left: #ffcc16 solid 10px; border-right: #ffcc16 solid 10px; text-align:center "><font color="#3f3d3d">PROJECT DELIVERABLES</font></div>
  
 
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<b>14 Jan 2018:</b> Proposal submission - 23:59
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<b>14 Jan 2018:</b> Proposal Submission - 23:59
:wikipage - 5%
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:Wikipage - 5%
:proposal report - 10%<br /><br />
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:Proposal Report - 10%<br /><br />
<b>25 Feb 2018</b> Interim report - 23:59
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<b>25 Feb 2018</b> Interim Report - 23:59
:interim report (wikipage) - 5%
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:Interim Report (wikipage) - 5%
:analytical sandbox - 15%<br /><br />
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:Analytical Sandbox - 15%<br /><br />
<b>26 Feb 2018 - 4 Mar 2018: </b> Interim presentation - (08:30 – 11:30, 13:30-17.30)
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<b>26 Feb 2018 - 4 Mar 2018: </b> Interim Presentation - (08:30 – 11:30, 13:30-17.30)
:interim presentation - 10%<br /><br />
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:Interim Presentation - 10%<br /><br />
<b>01 Apr 2018:</b> Undergraduate conference abstract submission - 23:59
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<b>01 Apr 2018:</b> Undergraduate Conference Abstract Submission - 23:59
:conference abstract - 5%<br /><br />
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:Conference Abstract - 5%<br /><br />
<b>08 Apr 2018: </b> Undergraduate conference full paper submission - 23:59
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<b>08 Apr 2018: </b> Undergraduate Conference Full Paper Submission - 23:59
:conference paper - 20%
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:Conference Paper - 20%
:poster - 10%<br /><br />
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:Poster - 10%<br /><br />
<b>14-15 Apr 2018: </b> Undergraduate conference days - (09:00 - 18:00)<br /><br />
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<b>12-13 Apr 2018: </b> Undergraduate Conference Days - (09:00 - 18:00)<br /><br />
<b>22 Apr 2018: </b> Final submission - 23:59
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<b>15 Apr 2018: </b> Final Submission - 23:59
:analytical sandbox and code - 15%
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:Analytical Sandbox and Code - 15%
:wikipage - 5%<br /><br />
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:Wikipage - 5%<br /><br />
  
 
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Latest revision as of 20:47, 15 April 2018

HOME

PROJECT OVERVIEW

DATA ANALYSIS

DOCUMENTATION

RECOMMENDATIONS

ABOUT US

BACK TO MAIN ANLY82


 

PROJECT DESCRIPTION


Data visualization software is a powerful analytical tool. With the necessary data, an ideal set of visualizations provides clear information about sales trends and operational data and is highly adaptable to users’ changing needs. This helps businesses better understand their strengths, weaknesses, and performance against competitors, and make quicker and more effective business decisions. A competitive edge is thus obtained against users of primitive data visualization methods, such as static charts and graphs - which are less customizable, take more time to update and provide less information in the long run.
This project will explore the benefits of data visualization improvements on a client, which is a well-established Fast-Moving Consumer Goods (FMCG) company. The study will use actual data for distribution, sales, Key Performance Indicators (KPIs) and price between 2014 and 2017. The data is currently visualized in a simple Excel dashboard, which provides limited information. In this project, we begin with data-cleaning and transformation processes in converting raw data into the flat data structure necessary for visualization, then assess the suitability of two more powerful and sophisticated visualization methods – Tableau and Qlik Sense. Finally, we recommend the platform which best suits the client’s needs, along with plans and recommendations for the client moving forward.
As a project team, we aim to improve our client’s data processing and analytics methods to improve their efficiency, provide clearer and more dynamic visualizations, and allow them to make improved marketing decisions.



PROJECT STATUS


100% completed

   


Group15timeline.PNG


PROJECT DELIVERABLES

14 Jan 2018: Proposal Submission - 23:59

Wikipage - 5%
Proposal Report - 10%

25 Feb 2018 Interim Report - 23:59

Interim Report (wikipage) - 5%
Analytical Sandbox - 15%

26 Feb 2018 - 4 Mar 2018: Interim Presentation - (08:30 – 11:30, 13:30-17.30)

Interim Presentation - 10%

01 Apr 2018: Undergraduate Conference Abstract Submission - 23:59

Conference Abstract - 5%

08 Apr 2018: Undergraduate Conference Full Paper Submission - 23:59

Conference Paper - 20%
Poster - 10%

12-13 Apr 2018: Undergraduate Conference Days - (09:00 - 18:00)

15 Apr 2018: Final Submission - 23:59

Analytical Sandbox and Code - 15%
Wikipage - 5%