Learn with data analytics problem

1. SHOPPING MALL
DATA VISUALISATION
AND ANALYSIS

2. PROBLEM STATEMENT
 The dataset has over 8000 rows and 14 columns.
 It a collection of data about approximately1550 products across 10 stores in
different cities of Canada.
 Analyze the patterns related to product sales.
 Use this data to explore functions in Tableau and Python for data analysis.

3. Data Visualization
(Tableau)

4. Tableau
 It is a data visualization tool.
 Every operations can be performed using drag and drop functionality. No coding
required.
 It can connect with different data sources such as files, relational databases and
others. .xls files used in this analysis.
 It can modify the data. For instance, new fields can be created using different
operations.
 It can split, join, concatenate, change data type and perform other such tasks.
 Provides numerous types of graphs and can perform sum, average, median, mode
and other such functions on data provided.

5. Setting up Tableau
 Download Tableau: https://www.tableau.com/products/desktop/download
 The next step will be set up the Tableau and import the data set:

6. Creating New Columns
 New fields can be created from existing ones. Calculations like divide, multiply,
addition, subtraction and others can be performed on numerical fields.

7. Split Function

8. After Split

9. Functions
 Apply various functions on numeric value columns while plotting.

10. Annotation
 Annotate the marks on trend lines.

11. Trend
Prediction
Across all the
stores, Low
Fat items had
greater sales
and Visibility.
As the
number of
low fat items
will increase,
the sales of
that item and
store will
also incline.

12. Types of graphs in Tableau
 Histogram
 Scatter Plot
 Packed Bubbles
 Line Graph
 Horizontal Histogram
 Tree Map
 Pie Chart
 Gantt Chart
 Box Plot and others.

13. Trend 1
Features
Toronto has
maximum
Sales and
Population
City with
second
highest
sales is
Ottawa and
Barrie has
lowest
sales.

14. Trend 2
Prediction
Low Fat items marked by blue
circles are bought more than
regular items.
As the number of
low fat items will
increase, the sales
of that item and
store will also
incline.

15. Trend 3
Features
Toronto
store sells
almost 35K
Snack food
items and
15K Soft
Drink items
in a month.
Barrie
and
Waterloo
sell least
number
of items.

16. Trend 4
Prediction
It shows
the variety
of items
available
at each
store type.
Increasing
the variety
of items at
a store will
increase its
sales.

17. Trend 5
Features
Item Prices
compared
for different
cities.
Fruits and
vegetables
most
expensive in
London.
Frozen foods
being most
affordable in
Barrie.

18. THANK YOU!!