The document presents an introduction to predictive analytics, discussing what predictive analytics is, its impact on business through examples like customer retention, and the engineering aspects of working in predictive analytics such as following the CRISP process and using tools like IBM SPSS. It also provides an example of using logistic regression for telecommunications churn prediction.

1. © 2014 IBM Corporation
Introduction to Predictive
Analytics : Business Impact
and Engineering Aspects
Mohamed Baddar- Software Engineer
1 September 2014

2. © 2014 IBM Corporation2
About the Speaker (Mohamed Baddar)
 Software Engineer at IBM Cairo ATG group for 6 years
mbaddar@eg.ibm.com
 Masters in statistical data mining- CSED – 2013 – Faculty of Engineering Alexandria -Egypt
 BSc in CSED – 2008 - Faculty of Engineering Alexandria –Egypt
 Working Areas
– Big data
– Analytics
– HPC

3. © 2014 IBM Corporation3
Table of contents/Agenda
1. What is Predictive Analytics
2. Impact on Business
3. Engineering Aspects
4. Examples
5. Questions
Source: If applicable, describe source origin
IBM Presentation Template Full Version

4. © 2014 IBM Corporation4
What is Analytics ?
 Discovering Patterns in data that has meaningful insights for stakeholders
 For example , pattern can be the relation between different factors, like salary , age , position
 Also it can be the trend (increase/decrease) of a factor , for example : an increase/decrease
in demand/sales rate of a specific product.
[source : http://accuracylabs.com]
What is Predictive Analytics ?
Source: If applicable, describe source origin

5. © 2014 IBM Corporation5
What is Predictive?
 Predicting a field from another
 For example , predict credit level from employee salary , credit history , demographic
information
 Group customers based on demographic information and purchase behavior
 Predict future sales from historical data , for example : given my years of experience in some
working environment, what is my salary (Regression model)
[source : http://iainstitute.org/en/learn/research/salary_survey_2012.php]
What is Predictive Analytics ?
Source: If applicable, describe source origin

6. © 2014 IBM Corporation6
Tell me exact applications to Predictive Analytics, please ?
Impact on Business?
Source: http://www.predictiveanalyticsworld.com/businessapplications.php

7. © 2014 IBM Corporation7
Seems good , any numeric examples?
Impact on Business?
Source: http://www.predictiveanalyticsworld.com/customer_retention.php
 Retaining New Customers

8. © 2014 IBM Corporation8
I am a Software Engineer , why I should work in this area ?
Engineer aspects
Source: http://www.predictiveanalyticsworld.com/businessapplications.php
 Apply Data Mining , statistics , Machine Learning Skills , not just software skills
 Market share of predictive analytics is increasing , hence increasing demand on software
engineer with analytics background
 Big companies trend to focus in this area
– List of top predicative analytics companies
http://www.predictiveanalyticstoday.com/top-business-intelligence-companies/

9. © 2014 IBM Corporation9
CRISP Process
Engineering Aspects
Source: ftp://9.17.248.40/software/analytics/spss/support/Modeler/Documentation/14/UserManual/CRISP-DM.pdf
 This is the standard process for working in any predictive analytics project

10. © 2014 IBM Corporation10
Technologies for Predictive Analytics:
Engineering Aspects
 IBM SPSS
http://www-01.ibm.com/software/analytics/spss/
 SAS: Business Analytics and Business Intelligence Software
http://www.sas.com/en_us/home.html
 The R Project for Statistical Computing
http://www.r-project.org/
 Stata : Data Analysis and Statistical Software
http://www.stata.com/

11. © 2014 IBM Corporation
Telecommunications Churn (Binomial Logistic Regression)
Example
 Logistic regression
source : http://en.wikipedia.org/wiki/Logistic_regression