As one of the largest offices supplies businesses in the UK, Office Team has grown rapidly through structured acquisitions and organic growth: Data Analysis Assignment, LSBP, Singapore

University London School of Business and Finance (LSBF)
Subject Data Analysis

As one of the largest office supplies businesses in the UK, Office Team has grown rapidly through structured acquisitions and organic growth. Founded in 1888, the business now has over 12,000 customers providing them with a wide range of managed services and over 100k different products.

Today they provide their customers with a single trusted source for their business supplies requirements. Their expert teams operate under specialist brands, while as a Group they lead the market by providing the most extensive portfolio of business supplies and services – available via a single online portal.

Task 1: Download the dataset salesdata.xlsx and create a workflow in Orange for the following

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 VAR model, set optimize AR model as ‘None’, and Add the 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 the 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 to improve the financial gains and help set goals for growth.

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