CRISPDM Reference Model Anna Mc Cuskey SIX PHASES

CRISP-DM Reference Model Anna Mc. Cuskey

SIX PHASES OF CRISP-DM REF MODEL Business Understanding Data Preparation Modeling Evaluation Deployment

PHASE ONE: BUSINESS UNDERSTANDING • Determine business objectives • Background, Business Objectives, Business Success Criteria • Assess Situation • Inventory of Resources, Requirements, Assumptions, Constraints, Risks & Contingencies, Terminology, Costs & Benefits • Determine Data Mining Goals • Data Mining goals, Data Mining Success Criteria • Produce Project Plan • Project Plan, Initial Assessment of Tools & Techniques

PHASE TWO: DATA UNDERSTANDING • Collect Initial Data • Initial Data Collection Report • Describe Data • Data Description Report • Explore Data • Data Exploration Report • Verify Data Quality • Data Quality Report

PHASE THREE: DATA PREPARATION • Data Set • Select Data • Rationalize for Inclusion/Exclusion • Clean Data • Data Cleaning Report • Construct Data • Derived Attributes, Generated Records • Integrate Data • Merged Data • Format Data • Reformatted Data

PHASE FOUR: MODELING • Select Modeling Technique • Modeling Technique & Assumption • Parameter Settings, Model Description • Model Assessment, Revised Parameter Settings • Generate Text Design • Build Model • Assess Model

PHASE FIVE: EVALUATION • Evaluate Results • Assessment of Data Mining Results • Review Process • Determine Next Steps • List of Possible Actions, Decision

PHASE SIX: DEPLOYMENT • • Plan Deployment Plan Monitoring & Maintenance Produce Final Report Review Project • Experience Documentation

SUMMARIZATION OF TASKS/OUTPUTS

DATA MINING TECHNIQUES Techniques that can be used together to solve a business problem. Data Description & Summarization Segmentation Concept Descriptions Classification Prediction Dependency Analysis