| University | London School of Business and Finance (LSBF) |
| Subject | Data Analytics |
Task 1
Using pivot tables, find out Region wise customer-wise total sales, and average sales. Which region did more sales and which region did fewer sales?
Record your answer along with the pivot table.
Use a line chart widget to visualize the trends and look for consistent trends. Analyze the line chart output for both region and aggregate sales, with respect to business insights and provide your recommendations.
Task 2
Calculate a mean Profit across Order Year and Order Priority using a pivot table. Insert the Select Columns widget and choose the column for High as the target variable and Order Year as the only Feature. Use the As Timeseries widget and create a Vector Auto Regressive model, set optimize Auto Regressive model as ‘None’, and Add trend vector as ‘Constant and Linear’. Add a Line chart widget after the VAR model and notice the forecasted values.
Connect from As Timeseries widget as Time series to the line chart widget and from the VAR model widget to Line Chart as Forecast.
For task 2, describe the trends in sales across time and derive business insights from the data. Combine your insights to give deeper pattern recognition.
Task 3
Identify relationships between profit & loss & shipping cost and derive business insights from the data, by describing outliers, clusters, and patterns you observe.
Task 4
Address one dilemma or challenge faced related to the business.
Task 5
Highlight 1 strength and 1 weakness of the business
Task 6
Suggest 1 limitation of the data and suggest 1 solution/improvement
Task 7
Discuss how a data science team can help the business improve its financial gains and help set goals for growth.
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