Difference between revisions of "ANLY482 AY2017-18T2 Group18/TeamDAcct Scope"

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The steps in detail are as follow:
 
The steps in detail are as follow:
 
[[Image:scopev1.png|800px|center]]
 
[[Image:scopev1.png|800px|center]]
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'''Problem Definition:'''
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'''Problem Identification:'''
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To sit down with client and to discuss about business problems that need to be solved.
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To sit down with client and discuss about the business problems that need to be solved. Thereafter to identify the pertinent business issues/questions that the company is currently facing.
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'''Data Preparation:'''
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To acquire/collect, clean, transform and integrate data (ETL) into a suitable form for further analysis.
  
 
'''Data Exploration:'''
 
'''Data Exploration:'''
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To summarize the main characteristics of a dataset.
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To perform exploratory data analysis (EDA) to analyse the data sets to summarise their main characteristics.
  
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'''Data Preparation:'''
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'''Insights Discovery:'''
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To collect, prepare, clean and integrate data into a suitable form for further analysis and processing.
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From uncovering patterns, trends in data through data exploration, to form insights and make actionable recommendations/responses in model selection. This allows us to better focus analytical efforts into variables/areas related to the business issues identified.
  
 
'''Model Selection:'''
 
'''Model Selection:'''
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To come up with models based on the type of business problems that we are dealing with.
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To come up with models based on the type of business issues/questions identified.
  
 
'''Model Validation:'''
 
'''Model Validation:'''
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To verify sensitivity analyses against resource-to-sales relationships as proposed in our model.
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To estimate model performance by verifying sensitivity analyses between actual and predicted outcomes.
  
 
'''Model Development:'''
 
'''Model Development:'''
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To build the most suitable model after validation is done and to test it against data we have on hand.
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To choose the most suitable model after validation is done and test it against new data we have on hand.
  
 
'''Communication of Results:'''
 
'''Communication of Results:'''
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To use information displays such as tables and charts to help communicate key messages contained in the data to the client.
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To communicate to the client and illustrate key insights contained in the data analysed using visualization tools.
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As agreed with our supervisor, our team has decided to divide the scope of work accordingly:
 
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'''Analysis of Invoice Detail Report:'''
 
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*Analyze sales trend over the years. Look for sales pattern and analyze data to understand what drives the sales trend.
 
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*Understand which channel contributes most to the company’s sales. Analyze the channels individually to find out what products in what therapy areas are they more likely to buy.
 
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*Find out what are the products that contributes the most to the company’s sales. Focus on these products in the later part of the analysis.
 
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'''Analysis of Customer Interactions:'''
 
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*Analyze customer interaction trends in terms of number of records and total duration of interactions.
 
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*Analyze which products are designated with the longest duration of interactions.
 
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'''Analysis of Sensitivity of Sales to Customer Interactions:'''
 
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*Compare total sales amount and duration of interactions and look for correlation.
 
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*Analyze sensitivity of sales according to different channels, therapy areas, as well as products.
 
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Revision as of 17:30, 13 January 2018

300px

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General Scope

In the validation of the current work done by the previous team, we would need to break down their findings into relationship pairs that they have examined, and from there derive any missing relationships between sales and various key resources that the client invests. This serves also as a primary sensitivity test, allowing us to better focus analytical efforts into areas which appear to have greater sensitivity.

The steps in detail are as follow:

Scopev1.png

Problem Identification: To sit down with client and discuss about the business problems that need to be solved. Thereafter to identify the pertinent business issues/questions that the company is currently facing.

Data Preparation: To acquire/collect, clean, transform and integrate data (ETL) into a suitable form for further analysis.

Data Exploration: To perform exploratory data analysis (EDA) to analyse the data sets to summarise their main characteristics.

Insights Discovery: From uncovering patterns, trends in data through data exploration, to form insights and make actionable recommendations/responses in model selection. This allows us to better focus analytical efforts into variables/areas related to the business issues identified.

Model Selection: To come up with models based on the type of business issues/questions identified.

Model Validation: To estimate model performance by verifying sensitivity analyses between actual and predicted outcomes.

Model Development: To choose the most suitable model after validation is done and test it against new data we have on hand.

Communication of Results: To communicate to the client and illustrate key insights contained in the data analysed using visualization tools.

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