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Search Results
| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
MIS 6371 (Overall) | |||||
B+ | |||||
MIS 6371 Naser Islam | |||||
B+ | |||||
Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
MIS 6371 (Overall) | |||||
B+ | |||||
MIS 6371 Naser Islam | |||||
B+ | |||||
SAP Cloud Analytics
MIS 6371
Naveen Jindal School of Management
The course allows students to learn about the capabilities of SAP Analytics Cloud that combines business intelligence, planning, predictive, and augmented analytics capabilities into one cloud environment to support business processes. Students also learn about SAP AI technologies and an in-memory database, which are part of the SAP Analytics Cloud. Students will also learn about Augmented Analytics which helps users ask questions in a conversational manner and get instant results explained in natural language, detect drivers of a KPI and take the best action using automated machine learning that discovers unknown relationships in data and predict outcomes, generate forecasts and automate predictive planning. Students also learn about the modeling environment to create planning models and import data, as well as the standard planning features available in the story. Advanced planning capabilities like value-driver trees, data actions, advanced formulas, and allocations, combined with Smart Predict, an environment to create and train predictive models. 3 credit hours.
Offering Frequency: Each semester
Grades: 43
Median GPA: B+
Mean GPA: 3.302
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SAP Cloud Analytics
MIS 6371
Naveen Jindal School of Management
The course allows students to learn about the capabilities of SAP Analytics Cloud that combines business intelligence, planning, predictive, and augmented analytics capabilities into one cloud environment to support business processes. Students also learn about SAP AI technologies and an in-memory database, which are part of the SAP Analytics Cloud. Students will also learn about Augmented Analytics which helps users ask questions in a conversational manner and get instant results explained in natural language, detect drivers of a KPI and take the best action using automated machine learning that discovers unknown relationships in data and predict outcomes, generate forecasts and automate predictive planning. Students also learn about the modeling environment to create planning models and import data, as well as the standard planning features available in the story. Advanced planning capabilities like value-driver trees, data actions, advanced formulas, and allocations, combined with Smart Predict, an environment to create and train predictive models. 3 credit hours.
Offering Frequency: Each semester
Grades: 43
Median GPA: B+
Mean GPA: 3.302
Click a checkbox to add something to compare.