Introducing Analytics with SAS Enterprise Miner. Matthew Stainer Business Analytics Consultant SAS Analytics & Innovation practice

Transcription

1 Introducing Analytics with SAS Enterprise Miner Matthew Stainer Business Analytics Consultant SAS Analytics & Innovation practice

2 FROM DATA TO DECISIONS Optimise Competitive Advantage What is the best that can happen? What if these trends continue? Forecast What will happen next? Predict Why is this happening? Statistical Analysis Alerts What actions are needed? Raw data Clean data Standard reports Ad hoc reports Query drill down Degree of Intelligence Where exactly is the problem? How many, how often, where? What happened?

3 Advanced Analytics Use Cases Response Modeling Cross and Up Selling Churn Prediction Customer Segmentation KPI Forecasting Customer Lifetime Value Web Mining Credit Scoring Fraud Detection Marketing Optimization Market Basket Analysis Customer Link Analytics Social Media Analytics Location Analysis Marketing Mix Analysis Copyr i g ht 2013, SAS Ins titut e Inc. All rights res er ve d.

4 SAS ENTERPRISE MINER DEVELOPED FOR Flexibility Accuracy Scoring Productivity

5 ANALYTICS LIFECYCLE MULTIPLE USER ROLES BUSINESS MANAGER Domain Expert Makes Decisions Evaluates Processes and ROI EVALUATE / MONITOR RESULTS IDENTIFY / FORMULATE PROBLEM DATA PREPARATION BUSINESS ANALYST Data Exploration Data Visualization Report Creation DEPLOY DATA EXPLORATION IT SYSTEMS / MANAGEMENT Model Validation Model Deployment Model Monitoring Data Preparation VALIDATE BUILD TRANSFORM & SELECT DATA MINER / STATISTICIAN Exploratory Analysis Descriptive Segmentation Predictive Modeling

6 SAS Model Manager SAS Visual Analytics Model Scoring Model package Export options (BASE SAS, C, Java) Scoring Accelerators SAS Data Management SAS Enterprise Miner

7 SAS PREDICTIVE ANALYTICS FACTORY SOURCE / OPERATIONAL SYSTEMS DATA PREPARATION DEVELOPMENT DEPLOYMENT MANAGEMENT Copyr i g ht 2013, SAS Ins titut e Inc. All rights res er ve d.

8 SAS ENTERPRISE MINER PROCESSING OPTIONS SAS Enterprise Miner SERVER (Traditional) SAS GRID MANAGER (On-premise Grid) SAS HIGH- PERFORMANCE DATA MINING (In-memory) SAS Model Manager SAS Scoring Accelerator (In-database)

9 SAS Enterprise Miner nodes SAMPLE Append Data Partition File Import Filter Merge Sample Input Data EXPLORE MODIFY Association Graph Variable DMDB Market Basket Link Analysis All of these HP nodes are automatically multithreaded, spreading Variable Explore Clustering SOM/Kohonen processing MultiPlot Selection Cluster StatExplore Path Analysis across the cores on your machines. Interactive Principal Rules Transform Drop Replacement All of these procedures Impute Binning are documented Componentsfor use outside of Builder the SAS Variables Enterprise Miner interface. Decision Tree AutoNeural Regression Neural Network Partial Least Squares Dmine Regression DM Neural Ensemble Rule Induction Gradient Boosting LARS MBR Two Stage Model Import Incremental Response Survival Analysis Credit Scoring** TS Correlation TS Data Prep TS Dimension Reduction TS Decomp. TS Similarity TS Exponential Smoothing HP Explore HP Impute HP Regression HP Transform HP Variable Selection HP Neural HP Forest HP Decision Tree HP Data Partition HP GLM HP SVM HP Cluster HP Principal Components ASSESS Cutoff Decisions Model Comparison Score Segment Profile UTILITY Control Point End Groups Start Groups Open Source Integration Reporter Score Code Export Metadata SAS Code Ext Demo Save Data Register Metadata Copyr i g ht 2013, SAS Ins titut e Inc. All rights res er ve d. HP = high-performance. **Requires Credit Scoring for SAS Enterprise Miner Add-on License.

10 Demonstration

11 SUMMARY DATA MINING SOLUTION FOR OPERATIONAL S Best predictions Comprehensive set of modelling techniques with flexible parameters Open design (SAS Code Node + Extension Nodes + External models) Collaborative platform Quick development One-click model development functionality Advanced model comparison to choose the best model quickly High Performance in-memory modelling option for fast development Easy deployment Models registered in the centralised repository Score code generated for in-database scoring Seamless integration with other SAS Solutions for scoring in batch or real-time

12 communities.sas.com/data-mining Thank You