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| 02/02 - 05/18 | ||||||
| M | T | W | Th | F | Sa | Su |
5:30 pm 5:30 pm |
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Subject: Software Eng (Grad) (SEIS)
CRN: 20305
CoFlex:In Person&Online Sync | Lecture
St Paul: Owens Science Hall 257
Online
Requirements Met:
Software Data Mgmt Conc
Software Technical Elective
This course focuses on database management system concepts, database design, and implementation. Conceptual data modeling using Entity Relationships (ER) is used to capture the requirements of a database design. Relational model concepts are introduced and mapping from ER to relational model is discussed. Logical database design, normalization, and indexing strategies are also discussed to aid system performance. Structured Query Language (SQL) is used to work with a database using the Oracle platform. The course also covers query optimization and execution strategies, concurrency control, locking, deadlocks, security, and backup/recovery concepts. Non-relational databases are also briefly introduced. Students will use Oracle and/or SQL Server to design and create a database using SQL as their project.
3 Credits
| 02/02 - 05/18 | ||||||
| M | T | W | Th | F | Sa | Su |
5:30 pm 5:30 pm |
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Subject: Software Eng (Grad) (SEIS)
CRN: 20306
CoFlex:In Person&Online Sync | Lecture
St Paul: O'Shaughnessy Science Hall 329
Online
Requirements Met:
Software Data Mgmt Conc
Software Technical Elective
This course focuses on database management system concepts, database design, and implementation. Conceptual data modeling using Entity Relationships (ER) is used to capture the requirements of a database design. Relational model concepts are introduced and mapping from ER to relational model is discussed. Logical database design, normalization, and indexing strategies are also discussed to aid system performance. Structured Query Language (SQL) is used to work with a database using the Oracle platform. The course also covers query optimization and execution strategies, concurrency control, locking, deadlocks, security, and backup/recovery concepts. Non-relational databases are also briefly introduced. Students will use Oracle and/or SQL Server to design and create a database using SQL as their project.
3 Credits
| 02/02 - 05/18 | ||||||
| M | T | W | Th | F | Sa | Su |
5:30 pm 5:30 pm |
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Subject: Software Eng (Grad) (SEIS)
CRN: 20314
CoFlex:In Person&Online Sync | Lecture
St Paul: Schoenecker Center 310
Online
Requirements Met:
Software Data Mgmt Conc
Software Technical Elective
In today’s data-driven world, Data Scientists and Data Engineers must have a solid understanding of data warehousing concepts. Many of the most valuable data sets still reside in corporate data warehouses. While the fundamental principles of data warehousing have existed for decades, a growing number of companies are now migrating these workloads to the cloud. This course aims to provide students with hands-on experience using popular cloud-based tools and data formats to develop metrics and features for analytics and machine learning. To achieve this, the course will begin by exploring the design differences between relational systems and data warehouses. It will then delve into best practices and common challenges associated with working with data from various sources. Additionally, as enterprises increasingly invest in data governance, data lineage, and master and metadata management to preserve contextual information, these concepts will also be covered. Understanding these topics is essential for leveraging disparate sources of information effectively. Prerequisite: SEIS 630
3 Credits
| 02/02 - 05/18 | ||||||
| M | T | W | Th | F | Sa | Su |
5:30 pm 5:30 pm |
||||||
Subject: Software Eng (Grad) (SEIS)
CRN: 20315
CoFlex:In Person&Online Sync | Lecture
St Paul: Schoenecker Center 310
Online
Requirements Met:
Software Data Mgmt Conc
Software Technical Elective
In today’s data-driven world, Data Scientists and Data Engineers must have a solid understanding of data warehousing concepts. Many of the most valuable data sets still reside in corporate data warehouses. While the fundamental principles of data warehousing have existed for decades, a growing number of companies are now migrating these workloads to the cloud. This course aims to provide students with hands-on experience using popular cloud-based tools and data formats to develop metrics and features for analytics and machine learning. To achieve this, the course will begin by exploring the design differences between relational systems and data warehouses. It will then delve into best practices and common challenges associated with working with data from various sources. Additionally, as enterprises increasingly invest in data governance, data lineage, and master and metadata management to preserve contextual information, these concepts will also be covered. Understanding these topics is essential for leveraging disparate sources of information effectively. Prerequisite: SEIS 630
3 Credits