Difference between revisions of "ANLY482 AY2017-18 T2 Group15 Project Overview"

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[[ANLY482_AY2017-18_T2_Group15_Reflections|<font  face ="Helvetica" color="#3f3d3d"><strong> REFLECTION</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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::To address the company’s concerns as stated by their representatives, our group aims to add value to the company by helping them to discover the determinants of a stronger brand – the extent to which advertising impacts sales. This would give the company’s marketing team a clear view of the concrete steps to take so their brands achieve increased market share.
 
  
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::In addition, we aim to create a comprehensive information dashboard displaying statistics and analytics which will allow users to obtain a clear overview of sales trends, business outcomes from various marketing decisions, and other details to facilitate management’s decision-making process.
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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 Project Overview Version 1| <font color="#000000"><b>'''VERSION 1'''</b>]]
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::Our project methodology will consist of, but is not limited to, the following:
 
  
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:::1. '''Correlation Analysis'''
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::::Correlation Analysis will be done between Marketing Expenditure and Brand Equity Scores. This will show how a particular marketing action affects the sales of the various beverage brands.
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:::2. '''Market Basket Analysis '''
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::::This is an analysis between how the sales of different brands correlate to each other. One of the main deliverables of interest will be the analytics of cannibalization effects among the brands.
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:::3. '''Seasonality Trends'''
 
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::::We will analyze how sales fluctuate on a broader scale, such as during holiday months and seasons, as well as how marketing campaigns affect sales trends.
 
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::The main tool to be utilised will be JMP Pro 13. This tool is selected for its combination of statistical analyses capabilities and visualization features provided. The end deliverable will be an interactive, updatable (through synchronisation) HTML dashboard that is accessible through mobile devices.
 
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::Data visualization is an important tool in driving success in businesses. Because of the way our brains process information, certain methods of data presentation, such as clear charts and graphs, make it much easier to convey important information and concepts to an audience, as compared to spreadsheets and reports.
  
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::We will be working with data of all beverage products sold by the company in Singapore. In terms of data, we will be working mainly with Marketing and Sales data as our primary focus is to link these two segments meaningfully.
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::This is especially important for large companies, which have access to large amounts of data, as their data may hold crucial information on the business and the market. By adopting standardised processes of data cleaning, structuring and transformation, businesses can create visualisations which improve business decisions and efficiency.
 
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::The data we obtain from the company will include historical sales figures, marketing expenditure, market share in comparison with competitors, distribution split across the company’s various channels, and brand equity scores.
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::The selection of a suitable business intelligence (BI) analytics tool that fits the enterprise is critical to the success of any BI project of an organization. We visualize data for various purposes and these direct us to select and design visualization in particular ways that rely on software tools which support particular features. To simplify the process of the selection, we may classify the requirements based on their degree of necessity. Furthermore, there are also special considerations with regards to obtaining those specific features in a tool – the requirement of custom coding, purchase of an add-on product from third party or a special product edition. For this comparative study, the team will be basing their evaluation on this list of criteria in Table 1. While this may not be an exhaustive list of requirements for a visualization tool, it satisfies three main conditions that many, if not all, organizations require in their BI tool – ease of use, data connectivity, line-of-business fit.
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{| class="wikitable" align=center width=80% style="background:white;color:black;"
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  |+ style="font-weight:bold;"| Table 1: List of Visual BI Tool Criteria by Stephen Few
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    ! style="background:#ffcc16;color:black;"| Category
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  ! style="background:#ffcc16;color:black;"| Requirement
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  | 1. Visualizations
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  | Useful charts and their features
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  | 2. Interaction
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  | Ways in which the information that you're viewing or the visualization that you're using to view it can be easily modified to see things differently
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  | 3. Multi-chart Displays
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  | Combining multiple charts on a single screen for simultaneous viewing
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  | 4. Statistical Calculations
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  | Built-in descriptive statistical functions
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  | 5. Speed of Response
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  | The time it takes for operations to complete once initiated
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  | 6. Data Access and Integration
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  | The ability to access data from all useful sources and to integrate data sets with ease
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|-
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  | 7. Output and Content Management
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  | Ways in which information can be delivered to others
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  |8. Platform Options
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  | The devices on which the tool can be used
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  |9. Ease of Learning and Use
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  | The ease with which analysts of various types can learn to use the product
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  |10. Programmability
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  | The ability to easily and extensively customize and automate a particular set of analytical tasks for repeated use
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  |11. Advanced Features
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  | Support for data mining, collaborations, audit trails, etc.
  
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Latest revision as of 16:07, 15 April 2018

HOME

PROJECT OVERVIEW

DATA ANALYSIS

DOCUMENTATION

RECOMMENDATIONS

ABOUT US

BACK TO MAIN ANLY82


 

OUR MOTIVATIONS


Data visualization is an important tool in driving success in businesses. Because of the way our brains process information, certain methods of data presentation, such as clear charts and graphs, make it much easier to convey important information and concepts to an audience, as compared to spreadsheets and reports.
This is especially important for large companies, which have access to large amounts of data, as their data may hold crucial information on the business and the market. By adopting standardised processes of data cleaning, structuring and transformation, businesses can create visualisations which improve business decisions and efficiency.


LITERATURE REVIEW


The selection of a suitable business intelligence (BI) analytics tool that fits the enterprise is critical to the success of any BI project of an organization. We visualize data for various purposes and these direct us to select and design visualization in particular ways that rely on software tools which support particular features. To simplify the process of the selection, we may classify the requirements based on their degree of necessity. Furthermore, there are also special considerations with regards to obtaining those specific features in a tool – the requirement of custom coding, purchase of an add-on product from third party or a special product edition. For this comparative study, the team will be basing their evaluation on this list of criteria in Table 1. While this may not be an exhaustive list of requirements for a visualization tool, it satisfies three main conditions that many, if not all, organizations require in their BI tool – ease of use, data connectivity, line-of-business fit.
Table 1: List of Visual BI Tool Criteria by Stephen Few
Category Requirement
1. Visualizations Useful charts and their features
2. Interaction Ways in which the information that you're viewing or the visualization that you're using to view it can be easily modified to see things differently
3. Multi-chart Displays Combining multiple charts on a single screen for simultaneous viewing
4. Statistical Calculations Built-in descriptive statistical functions
5. Speed of Response The time it takes for operations to complete once initiated
6. Data Access and Integration The ability to access data from all useful sources and to integrate data sets with ease
7. Output and Content Management Ways in which information can be delivered to others
8. Platform Options The devices on which the tool can be used
9. Ease of Learning and Use The ease with which analysts of various types can learn to use the product
10. Programmability The ability to easily and extensively customize and automate a particular set of analytical tasks for repeated use
11. Advanced Features Support for data mining, collaborations, audit trails, etc.


OUR WORK PLAN


Work plan.png
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