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Course Name Course Code
Data Mining on CRM by using SAS 83
Course Contents

Statistical Techniques for Data Mining on Customer Response Models by using SAS ®


Program Objective

This program is designed to guide Statistical Analyst/Business analytics/SAS professionals in extracting implicit, previously unknown and potentially useful knowledge from large data sets, developing performance models & usage of optimization techniques.

Target Audience:

Managers Investors and decision makers of any kind involved with analytics, direct marketing or online marketing activities.

Marketers Personnel running or supporting direct marketing, response modeling, or online marketing who wish to improve response rates and increase campaign ROI for retention, up-sell and cross-sell.

Technology experts Analysts, developers, DBAs, Data warehouses, web analysts, and consultants who wish to extend their expertise to predictive analytics.


Program Benefits

The participants will acquire the knowledge on Applied Analytics using SAS/STAT/EG/ E-Miner.

After this training, participants will able to understand about basics knowledge of Statistics, data modeling: Missing Value Analysis, and Identification of Outliers in Univariate & Multivariate data sets, Data Visualization: Scatter Plots, Scatter Matrix, Histograms, Box Plots, etc. Predictive Modeling: Decision Tree, Linear Regression, Logistic Regression, Segmentation and Profiling: Market Basket Analysis: Frequent Item Set Generation & Association Rule Mining, Cluster Analysis: K Mean Clustering, Hierarchical Clustering Methods


Course Content


·         Business problems defining in technical term

·         Data Modeling

o   Identification of data source (selection)

o   Data integration (collating)

o   Data cleaning (Balancing)

o   Data transformations (scaling)

o   Imputation & replacement (modifying)

o   Identification of outliers in Univariate & Multivariate datasets


·         Data-Mining

§  Predictive Modeling

o   Developing models using Decision Tree Algorithms (CHAID & CART)

o   Regression Techniques (Simple Regression & Logistic Regression)

o   Decision Model Validation/ Decision model testing


§  Segmentations & Profiling

o   Market Basket Analysis (frequent item set generation & association rule mining)

o   Identification of Clusters (using K-Mean clustering & Hierarchical clustering Algorithms)


·         Technical interpretation Transform into Business Logics to prepare business report



Training Highlights:

1.     Program will be based on large data sets (2 Million cases)

2.     Program will be based on live CRM projects to understand client deliverables

3.     Program focus on

·         Business problems defining in technical term

·         Data Preparation (Data-modeling)

·         Data-Mining (Sampling, Exploring, Modification, Modeling, Assessment & model testing)

·         Technical interpretation Transform into Business Logics to prepare business report