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| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
BUAN 6345 Naser Islam | |||||
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| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
BUAN 6345 Naser Islam | |||||
Naser Islam
[email protected]Grades: 3,643
Median GPA: A-
Mean GPA: 3.444
2.5
Professor rating
3.1
Difficulty
71
Ratings given
19%
Would take again
SAP Analytics
BUAN 6345
Naveen Jindal School of Management
This course provides students with in-depth knowledge of In-memory Business Intelligence tools and In-memory databases using SAP. The course features the SAP Analytics portfolio of solutions that provides a comprehensive set of modern business intelligence, augmented analytics (including predictive analytics), and enterprise planning capabilities that work together to analyze, predict, plan, and report on data wherever it resides. Students learn about different options available to speed up the queries and why In-memory tools are important. The course covers both the semantic layer modeling and front-end visualization aspects of the In-memory BI tool used. The course also covers the DML, DDL, and modeling techniques used for the In-memory database used. Students learn such concepts using hands-on exercises and practical assignments. The course requires a solid understanding of ER and dimensional modeling. Non-Enroll credit hours.
Offering Frequency: Each year
Grades: 33
Median GPA: A-
Mean GPA: 3.576
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Naser Islam
[email protected]Grades: 3,643
Median GPA: A-
Mean GPA: 3.444
2.5
Professor rating
3.1
Difficulty
71
Ratings given
19%
Would take again
SAP Analytics
BUAN 6345
Naveen Jindal School of Management
This course provides students with in-depth knowledge of In-memory Business Intelligence tools and In-memory databases using SAP. The course features the SAP Analytics portfolio of solutions that provides a comprehensive set of modern business intelligence, augmented analytics (including predictive analytics), and enterprise planning capabilities that work together to analyze, predict, plan, and report on data wherever it resides. Students learn about different options available to speed up the queries and why In-memory tools are important. The course covers both the semantic layer modeling and front-end visualization aspects of the In-memory BI tool used. The course also covers the DML, DDL, and modeling techniques used for the In-memory database used. Students learn such concepts using hands-on exercises and practical assignments. The course requires a solid understanding of ER and dimensional modeling. Non-Enroll credit hours.
Offering Frequency: Each year
Grades: 33
Median GPA: A-
Mean GPA: 3.576
Click a checkbox to add something to compare.