Data Visualization Project: Sales, Profit, and Shipping Analysis

This project presents a comprehensive data visualization analysis of sales, profit, and shipping data using various charts and dashboards. The analysis includes a profit map color-coded by average profit across countries, filtered by region. Sales by subcategory are displayed using treemaps, with ...Read More

USIP3
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The Profit map for the
company’s business
across several countries
is presented and is
colour coded with deep
blue representing the
highest Average profit
and dark red the lowest
average profit. Filters
are added for the north,
south and central
regions of individual
countries.

Sum of sales by
subcategory is
displayed with filters
for region and year
of order. The region
filter is colour coded
for the different
regions. It is seen
that Bookcases,
Copiers, Phones and
Storages lead the
sales chart.

Dashboard representing the sales by product subcategory and the profit
map. The filter in the map works by indicating for both the sheets the
required parameter of interest.

The Sale by Subcategory
is represented by a
treemap. The profit is
added in the tooltip.
Bookcases have the
highest sales and Labels
have the lowest sales.
The treemap is filtered by
region and Oder Date in
years.

A map of the regions
and the corresponding
sales. Deeper blue
indicates higher sales.
Central and a few
southern regions have
higher sales while
region show relatively
low sales.

A treemap for Product
Profit And Sales b
Segment indicating that
the distribution of Sales
across the different
segment of products i.e
Consumer, Corporate,
and Corporate. The
treemap is color coded to
visually identify the
performance in different
segments.

A sale by Product category heat map is color
coded with dark to lighter spectrum of grey.
Products under technology have the highest
sales and products under Furniture have the
lowest sales.

An overview
dashboard consisting
of the Profit map, the
Map of Sales by
region, and the sales
by region. The Profit
and Sales maps are
color coded and
deeper color
differentiates the
regional parameters
that we are interested
in.

Customer Dashboard
showing Customer Ranking
based on Profit Ratio. A
treemap of product profit
and sales and segment,
and a scatterplot of sales
and profits by name.

An area chart indicating
the overall shipping
performance. The figure
gives us an idea about
the proportion of
shipping done before,
on or after the
scheduled time. It can
be seen that overall the
proportion of products
shipped early has been
the highest.

Shipping trend area chart showing the
sale in the Central region. The color
codes are blue for shipped early,
yellow for shipped late and red for
shipped late. It can be seen that most
products were shipped early between
week 30 and 40 and again between
week 45 and 50.

Shipping status in the north region.
The data in x axis represents the
week of order date and the y axis
indicates the number of records . .
The color codes are blue for shipped
early, yellow for shipped late and
red for shipped late .Highest
proportion of shipped late orders
were between week 35 to 40 and
week 42 to week 50.

Shipping status in Southern
region. The data in x axis
represents the week of order
date and the y axis indicates the
number of records . The color
codes are blue for shipped early,
yellow for shipped late and red
for shipped late For the southern
region the highest bulk of
Shipped Late orders were
between week 45 to 50.

Percentage of total number of records. The data is presented in a bar chart
which also indicates separately the percent of orders shipped early, shipped
late and shipped on time.

A shipping dashboard
displaying shipping status on
one image and the proportion
of each on the other.

The latest year
sales is compared
with the prior
year sales using a
bar chart and
adding a
reference line.
The data is
filtered on region
by Central, North
and South. The
sale is arranged
in descending
order by latest
sales.

The
individual
YoY
comparison
is done for
the North
Region. It is
seen that for
phones and
appliances
the prior
sales was
higher than
the latest
year sales.

The individual
YoY comparison
is done for the
Central Region. It
is seen that for
Appliances,
Furnishings,
Paper and
Envelopes the
prior year sales
was higher than
the latest year
sales.

The individual
YoY comparison
is done for the
South Region. It
is seen that for
Appliances,
Accessories,
envelopes and
table the prior
sales was
higher than the
latest year
sales.

References:
Al-Kassab, J., Ouertani, Z. M., Schiuma, G., & Neely, A. (2014).
Information visualization to support management decisions.
International Journal of Information Technology & Decision Making
Baldwin, D. (2016). Mastering Tableau. Packt Publishing Ltd.
Milligan, J. N. (2016). Learning Tableau 10. Packt Publishing Ltd.
Zheng, L. (2014). Data visualization.