UC2NDB10 NoSQL Databases

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UC2NDB10 NoSQL Databases

Course description
- NQF Level
  Bachelor's degree (Level 6 1. Cycle)
- Area of Study
  Computing
- Program of Study
  Applied Data Science
- ECTS
  10
- Campus
  Kristiansand, OnlinePLUS - Oslo, Online
- Course Leader
  Sahar Yassine

Introduction

Language of Instruction and assessment: English
May be offered on Campus and Online.
May be offered as a separate course.

Included in the following bachelor's degrees:

Applied Data Science

Course Aim(s)

The course provides a thorough appreciation for alternative, non-relational, data management technologies. This course will examine the different data technology paradigms encompassed by the NoSQL umbrella and gain an understanding of when and how to apply a variety of NoSQL technologies, including graph databases.

Course Learning Outcomes

Knowledge

The student has knowledge of

K1	historical and emerging developments of NoSQL data store theories and technologies.
K2	difference between relational and NoSQL database technologies.
K3	a selection of principal NoSQL data management technologies, including document databases, column stores, and graph databases.

Skills

The student gain skills in

S1	ability to critically evaluate and select appropriate NoSQL data management technologies.
S2	application of the underlying mathematical principles of NoSQL database technologies, including Graph Theory.
S3	design, develop and apply a NoSQL database system within a selection of Big Data-driven problematic situations.
S4	employ appropriate techniques for visualising and navigating NoSQL database content.
S5	critically evaluate the approach to, and results from, applying NoSQL technologies across a variety of situations.

General Competence

The student can demonstrate

G1	understanding the strengths and limitations of relational and NoSQL data models.
G2	ability to apply and communicate the results of a NoSQL approach to modelling data.
G3	critical reflection on the application and efficacy of a variety of data management technologies and challenges associated with their use.

Course Topics

Introduction to NoSQL
NoSQL Data Management
Further NoSQL Concepts and Developments
Developing NoSQL Solutions

Teaching Methods

Teaching will be based on a hybrid-flexible approach. Instructor-led face-to-face learning is combined with online learning in a flexible course structure that gives students the option of attending sessions in the classroom, participating online, or doing both.
All activities require active student participation in their own learning.
Learning delivery methods and available resources will be selected to ensure constructive alignment with course content, learning outcomes and assessment criteria.
Students will be taught using a mixture of guidance, self-study, and lecture material. Topics will be introduced in a series of weekly lectures. The guidance sessions will be directed practical exercises and reading in which students can explore topics with support from a teacher. This material will also require students to self-manage their time to ensure tasks are completed and the theory is fully understood. This will allow the students to fully engage with lectures and with their peers.

Resources and Equipment

Learning resources are available in the LMS and include, but is not limited to:
- literature and online reading material (essential and recommended)
- streams, recordings and other digital resources, where applicable
- video conferencing and communication platforms, if applicable
- tools, software and libraries, where applicable
Students must have access to an internet connection, and suitable hardware.
- Accessing live streams and virtual laboratories requires a minimum broadband connection of 2Mbps (4Mbps recommended).
Students working on their own laptop/computer are required to acquire appropriate communications software, e.g., webcam, microphone, headphones.

Prerequisite Knowledge

UC1DMA10 Discrete Mathematics, and UC1PR210 Programming and Databases, or equivalent course(s).

Reading List

The reading list for this course and any additional electronic resources will be provided in the LMS.

Study Workload

250 nominal hours.
Study workload applies to both Campus and Online students.

Activity	Duration
Teacher-led activity	24
Teacher-supported work	48
Self-study	178

Work Requirements

There are no mandatory assignments in this course.

Assessment Strategy

This course has five (5) exams contributing towards the overall and final grade of the course.

All exams must be assessed as passed to receive the final Course Grade.

Form of assessment	Grading scale	Grouping	Duration of assessment
Online Exam	A-F
Online Exam	A-F
Online Exam	A-F
Online Exam	A-F
Online Exam	A-F