Participants establish the process foundation for Data Preparation, Smart Discovery, and Analytic Readiness. The work is grounded in a commercial analytics team seeking defensible forecasts, driver analysis, and actionable insights from changing sales and margin data and contributes directly to explainable augmented analytics.
The instructor traces data preparation, feature selection, smart discovery, quality assessment through the scenario, explaining navigation, decisions, dependencies, system responses, and the evidence retained in augmented analytics data readiness workbook. The walkthrough also investigates the condition where a predictive driver appears influential because missing values were handled inconsistently.
Complete a controlled activity covering data preparation, feature selection, smart discovery, quality assessment and preserve the result in augmented analytics data readiness workbook.
Start at the earliest point where expected behavior differs from the observed result. Review process sequence, relevant data, configuration, authorization, integration, and timing as separate hypotheses. Treat “a predictive driver appears influential because missing values were handled inconsistently” as unconfirmed until settings, documents, logs, reports, and focused retesting support the cause.
Learners can apply Data Preparation, Smart Discovery, and Analytic Readiness, explain the resulting SAP behavior, and defend the outcome through augmented analytics data readiness workbook.