Course: SAP HANA Machine Learning: Logistics Routes Segmentation - AI-Tutor Powered
Learn how to use the SAP HANA Machine Learning K-Means grouping function included in the Predictive Analysis Library. We will find the logistics segments by analyzing multiple variables: 1) Distance of each delivery order 2) Weight 3) Month of delivery to know the season peaks. 4) Priority of delivery. We look at Grouping statistics concepts for the Optimal number of groups for data, Average point for each group, and Analyze groups by the number of records, and demanding services. We practice step-by-step SQL queries to execute the Grouping SAP Hana function.
Course: SAP HANA Machine Learning: Logistics Routes Segmentation - AI-Tutor Powered
Learn how to use the SAP HANA Machine Learning K-Means grouping function included in the Predictive Analysis Library. We will find the logistics segments by analyzing multiple variables: 1) Distance of each delivery order 2) Weight 3) Month of delivery to know the season peaks. 4) Priority of delivery. We look at Grouping statistics concepts for the Optimal number of groups for data, Average point for each group, and Analyze groups by the number of records, and demanding services. We practice step-by-step SQL queries to execute the Grouping SAP Hana function.
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Description
Learn how to use the SAP HANA Machine Learning K-Means grouping function included in the Predictive Analysis Library. We will find the logistics segments by analyzing multiple variables: 1) Distance of each delivery order 2) Weight 3) Month of delivery to know the season peaks. 4) Priority of delivery. We look at Grouping statistics concepts for the Optimal number of groups for data, Average point for each group, and Analyze groups by the number of records, and demanding services. We practice step-by-step SQL queries to execute the Grouping SAP Hana function.
