SAP Data Science – CRISP-DM

Business Understanding
> Determine Business Objectives
>> Background
>> Business Objectives
>> Business Success Criteria
> Access Situation
>> Inventory of Resources
>> Requirements, Assumptions & Contraints
>> Risks & Contingencies
>> Terminology
>> Costs & Benefits
> Determine Data Science Goals
>> Data Science Goals
>> Data Science Success Criteria
> Produce Project Plan
>> Project Plan
>> Initial Assessment of Tools & Techniques
Design Thinking – Empathize
Design Thinking – Design
Design Thinking – Ideate

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

Data Preparation
>> Dataset
>> Dataset Description
> Select Data
>> Rationale for Inclusion/Exclusion
> Clean Data
>> Data Cleaning Report
> Construct Data
>> Derived Attributes
>> Generated Records
> Integrate Data
>> Merged Data
> Format Data
>> Reformatted Data

Modeling
> Select Modeling Technique
>> Modeling Technique
>> Modeling Assumptions
> Generate Test Design
>> Test Design
> Build Model
>> Parameter Settings
>> Models
>> Model Description
> Assess Model
>> Model Assessment
>> Revised Parameter Settings
Design Thinking – Prototype

Evaluation
> Evaluate Results
>> Assessment of Data Science Results
>> Approved Model
> Review Process
>> Review of Process
> Determine Next Steps
>> List of Possible Actions
>> Decision
Design Thinking – Test

Deployment
> Plan Deployment
>> Deployment Plan
> Plan Monitoring & Maintenance
>> Monitoring Maintenance Plan
> Produce Final Report
>> Final Report
>> Final Presentation
> Review Project
>> Experience Documentation