INFO 7250 — Engineering of Big-Data Systems
4 semester hoursGraduateLectureusually offered: fall, springtypical days: WOnlineOnline
Introduces a general framework for thinking about big data. Services such as Web analytics and intelligent e-commerce have promoted a rapid increase in the volume of data generated, analyzed, and archived. In order to solve the problems related to big data, a newer type of database product has emerged. Covers how to apply technologies like Hadoop, Accumulo, MongoDB, and various NoSQL databases to build simple, robust, and efficient systems to manage and analyze big data. Also describes an easy approach to big data systems that can be built and run by a small team of students. Guides students through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they are built.
Prerequisites
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Fall 2024 | 1 | 21 | 50 | 42% | 29.0 |
| Spring 2025 | 1 | 9 | 50 | 18% | 41.0 |
| Fall 2025 | 1 | 6 | 50 | 12% | 44.0 |
| Spring 2026 | 1 | 4 | 30 | 13% | 26.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 48% · T 0% · W 53% · Th 0% · F 0%
Common patterns: W (53% of sections), M (48% of sections) — in patterns, R means Thursday
Professors
Fall
- Yusuf Ozbek (100% of students) · reviews
Spring
- Yusuf Ozbek (100% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (INFO course descriptions) · Student reviews on RateMyHusky · All INFO courses · Plan it at numap.app