Mit den Prognose-Funktionen von Smart Predict in SAP Analytics Cloud (SAC) nutzen Sie für Ihr strategisches Reporting die Algorithmen des maschinellen Lernens. Dieses Buch richtet sich gleichermaßen an SAC-(BI)-Anwender und Berater, Data Scientists wie auch an Business-Analysten, die sich mit den Predictive Analytics auf Basis ausgewählter Prognoseszenarien vertraut machen möchten.

Das Autorenduo startet mit den technischen Voraussetzungen, Restriktionen und den zentralen Smart-Predict-Komponenten. Im Rahmen der Implementierung stehen qualitätsgesicherte Quelldaten als wesentlicher Erfolgsfaktor für die Modellierung und das Trainieren von Prognoseszenarien, die zu untersuchende Zielvariable sowie deren abhängige Einflussfaktoren im Fokus. In diesem Kontext werden der Einsatz von Datensets, Variablen, Datenmodell, Szenario und der Prozess des Modelltrainings beschrieben.

Sie lernen die Prognosetypen Klassifikation, Regression sowie Zeitreihen und ihre Einsatzgebiete kennen und begleiten die praxisorientierte Anwendung der Prognoseszenarien auf ausgewählte Problemstellungen aus dem Geschäftsleben. An erfahrenere Datenwissenschaftler richtet sich der abschließende Exkurs über die spezielle Integration von R Visualisierung im Kontext von Smart Predict.

<br/>

– Grundlegende Konzepte und Komponenten im neuen Prognosetool der SAC

– Technische und fachliche Voraussetzungen für den Einsatz von Smart Predict

– Erstellung und Interpretation von Prognoseszenarien (Klassifikation, Regression und Zeitreihen)

– Predictive Forecasting: Smart-Predict-Beispiele in der Praxis

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