DATASCI 709 : Data Management

Science

2024 Semester One (1243) (30 POINTS)

Course Prescription

Data management is the practice of collecting, preparing, organising, storing, and processing data so it can be analysed for business decisions. The course will use R and SQL to illustrate the process of data management. This will include principles and best practice in data wrangling, visualisation, modelling, querying, and updating.

Course Overview

The course begins with an introduction to data governance, principles of data-analytic workflows, and data models commonly used in practice. Basic transformations of data structures are explained, and then performed using R and SAS. The concepts of cleaning data, creating derived variables for data models, processing text, and handling missing data are described, and applied to prepare data for analysis. The course provides an introduction to data management within relational database systems. SQL is treated in depth as the industry standard for defining, manipulating and querying data. Relational calculus is used as the de-facto language for soundly declaring  queries, while relational algebra is presented as the language for optimising the execution of queries. The course concludes by discussing principles and best practice in conceptual and logical database design. An advanced understanding of Entity-Relationship modelling is provided as basis for converting application requirements into blueprints of database models, which can be future-proofed for efficient data processing by techniques from database normalisation.   

Course Requirements

Prerequisite: COMPSCI 130, MATHS 108, and 15 points from STATS 101, 108, or equivalent Restriction: COMPSCI 351, 751, STATS 383, 707, 765

Capabilities Developed in this Course

Capability 1: People and Place
Capability 3: Knowledge and Practice
Capability 4: Critical Thinking
Capability 5: Solution Seeking
Capability 6: Communication
Capability 7: Collaboration
Capability 8: Ethics and Professionalism
Graduate Profile: Master of Data Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Demonstrate an understanding of data governance, ethics and analytic workflow principles (Capability 1, 3, 6, 7 and 8)
  2. Be able to understand and apply different data models (Capability 3, 4 and 5)
  3. Apply data structure transformations in R and SAS (Capability 3, 4 and 5)
  4. Apply data cleaning and feature generation techniques (Capability 3, 4 and 5)
  5. Be able to process text and handle missing data (Capability 3, 4 and 5)
  6. Demonstrate an understanding of database management systems and the relational model of data (Capability 3, 5 and 6)
  7. Apply SQL as the industry standard for defining, manipulating and querying data (Capability 3, 4, 5, 6 and 8)
  8. Use relational algebra for optimising the evaluation of database queries (Capability 3, 4 and 5)
  9. Apply relational calculus to soundly declare complex database queries (Capability 3, 4 and 5)
  10. Be able to apply and evaluate conceptual data modelling and normalisation theory to design high-quality relational databases (Capability 3, 4, 5, 6 and 8)

Assessments

Assessment Type Percentage Classification
Assignments 100% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6 7 8 9 10
Assignments

Tuākana

Tuākana Science is a multi-faceted programme for Māori and Pacific students providing topic specific tutorials, one-on-one sessions, test and exam preparation and more. Explore your options at
https://www.auckland.ac.nz/en/science/study-with-us/pacific-in-our-faculty.html
https://www.auckland.ac.nz/en/science/study-with-us/maori-in-our-faculty.html

Workload Expectations

This course is an online 30 point course and students are expected to spend 300 hours (equivalent to 150 hours for a standard 15-point course).

Delivery Mode

Online

The course may include live online events including group discussions and/or tutorials and these will be recorded.

Study material will be released progressively throughout the course.

This course runs to the University semester timetable and all the associated completion dates and deadlines will apply.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

The course is provided online via Canvas with links to necessary reading resources.

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

N/A, new course.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed for potential plagiarism or other forms of academic misconduct, using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Copyright

The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

The delivery mode may change depending on COVID restrictions. Any changes will be communicated through Canvas.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 01/11/2023 10:21 a.m.