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IS112

Data Management

1 CreditsTerm 2

Description

This course will cover fundamentals of relational database theory, important data management concepts such as data modelling, database design, database implementation in current business information systems, and some basic concepts related to unstructured data. A series of in-class exercises, tests, pop quizzes and a course project will help students understand the covered topics. Students are expected to apply knowledge learned in the classroom to solve many problems based on real-life business scenarios, while gaining hands-on experience in designing, implementing, and managing database systems. Students are also expected to understand the differences between structured data and unstructured data. This course is applicable to students declaring a major from SIS.

Requisites

Prerequisites: None

Co-requisites: None

Anti-requisites: IS105/DSA308 - Mutually Exclusive

Attributes

Department: SCIS

Course Level: Undergraduate

Tracks: N/A

Areas: Accounting Data and Analytics Core Accounting Electives Accounting Options Analytics Major Business Options Computing Studies Core Data Science and Analytics Electives Econ Major Rel/Econ Options Financial Forensics Core Grad Req - Dig Tech/Data Ana (Intake 2024 onwards) IT Solution Development Core Information Systems Core (Intake 2018 and earlier) Information Systems Core (Intake 2019 to 2023) Law Related Electives Smart-City Mgmt & Tech Core (Intake 2019 to 2021) Smart-City Mgmt & Tech Core (Intake 2022 onwards) Smart-City Mgmt &Tech Core (Intake 2018 & earlier) Social Sciences/PLE Major-related Tech for Business Core (Intake 2018 and earlier) Tech for Business Core (Intake 2019 - 2023) Technology & Entrepreneurship Technology Studies Cluster

Learning Outcomes

1) Explain the concepts of Entity-Relationship (ER) Model 2) Explain the concepts of Enhanced Entity-Relationship (EER) Model 3) Develop an EER model for a given application to support a given list of functions 4) Explain the concepts of relations and the seven steps required to transform a given ER/EER model to a relational schema 5) Apply the transformation from ER/EER models to relations in many scenarios 6) Explain the concepts of data normalization and the first three normal forms 7) Apply data normalization in many scenarios 8) Explain the Structured Query Language (SQL) 9) Demonstrate how to build a database and how to retrieve data from the database via MySQL 10) Build a database for a given scenario and write SQL statements to retrieve data from it 11) Explain the concepts of unstructured data and similarity search in text

Graduate Learning Outcomes

Disciplinary Knowledge, Critical thinking & problem solving

Competencies

Data Design, Design Thinking Practice, Software Design, Solution Architecture, Computational Modelling

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