1.
Predictive Analytics of
External Data
Predictive Analytics Use Case

2.
A company can determine the influence of the internal and
external data on sales and identify whether factors such as
GDP, rainfall or population are effective for the business.
Further appropriate action can be taken to increase sales or
ROI.
Predictive Analytics of External Data
Sample Application
Description

3.
Target
Sales
Predictive Analytics of External Data
Sample Application

4.
• GDP
• Rainfall
• Vacancy
• Wholesale gap
Influencing
Factors
Predictive Analytics of External Data
Sample Application

5.
Multiple Linear Regression is a technique that explores the
relationship between two or more independent variables
and one dependent variable.
• The higher the R-square value of a model(>=0.7), the
better the accuracy of the model.
• A lower R-square value of a model(<0.7) means the model
needs to be rebuilt using different input parameters or the
input dataset doesn't exhibit a structure suitable for
regression.
Algorithm(s)
Predictive Analytics of External Data
Sample Application

6.
Model
Visualisation
Predictive Analytics of External Data
Sample Application

7.
Model
Visualisation
Predictive Analytics of External Data
Sample Application

8.
Model
Visualisation
Predictive Analytics of External Data
Sample Application

9.
Model
Summary
Predictive Analytics of External Data
Sample Application

10.
Interpretation
Predictive Analytics of External Data
Sample Application

11.
Result
• Predicted Sales
Predictive Analytics of External Data
Sample Application

12.
Result
Sales prediction with accuracy value (R-square value) based on
advertisement expense, wholesale gap and vacancy can be
performed using APPLY functionality as shown below.
Predictive Analytics of External Data
Sample Application

13.
Result
Predictive Analytics of External Data
Sample Application

14.
Smarten – Predictive Analytics of External Data Use Case - 2019
Predictive Analytics of
External Data
Predictive Analytics Use Case
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