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Module Catalogue

IB9HP-15 Data Management

Department
Warwick Business School
Level
Taught Postgraduate Level
Module leader
Nursen Aydin
Credit value
15
Module duration
10 weeks
Assessment
Multiple
Study location
University of Warwick main campus, Coventry

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Introductory description

This module is designed to provide students with the foundational concepts, tools, and techniques required for effective data management, a critical competency for any analytics project. It is structured around two primary objectives: (a) to enable students to proficiently use datasets in analytics projects,, and (b) to equip students with the skills needed to construct and develop these datasets themselves.

Module web page

Module aims

The main aims of the module are to familiarise students with spreadsheets, relational databases, SQL and tools designed to work with big data.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Spreadsheets and interaction with the user
Relational databases
SQL queries
Big data technologies

Learning outcomes

By the end of the module, students should be able to:

  • Demonstrate an aptitude for working with big data technologies
  • Demonstrate comprehensive understanding of SQL
  • Use software packages to manipulate, transform and normalize data

Indicative reading list

Elmasri, Ramez, and Sham Navathe. Fundamentals of database systems. Pearson, 2017.
Gordon, Keith. Principles of Data Management: Facilitating Information SharingSecond Edition, British Computer Society Press, 2015.
Wickham, H., & Grolemund, G. R for data science: import, tidy, transform, visualize, and model data. O'Reilly Media, Inc. 2016.
Teate R. SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis. Wiley Books, 2021.

Subject specific skills

Design and write basic SQL statements
Work with datasets of various formats: structured and unstructured
Extract, manipulate, join and store data in databases
Read and write SQL queries and manipulate data using various programming tools

Transferable skills

Communcation skills
Problem solving

Study time

Type Required
Practical classes 9 sessions of 2 hours (12%)
Online learning (scheduled sessions) 9 sessions of 1 hour (6%)
Private study 51 hours (34%)
Assessment 72 hours (48%)
Total 150 hours

Private study description

Private study to include preparation for lectures

Costs

No further costs have been identified for this module.

You do not need to pass all assessment components to pass the module.

Assessment group D5
Weighting Study time Eligible for self-certification
Assessment component
Group Report and Presentation 40% 29 hours No

2000 words report and presentation
Reassessment component is the same
Assessment component
On-campus Examination 60% 43 hours No
  • Answerbook Pink (12 page)
Reassessment component is the same
Assessment group S
Weighting Study time Eligible for self-certification
Assessment component
Group Report and Presentation 40% 29 hours No
Reassessment component is the same
Assessment component
Individual Assignment 60% 43 hours No
Reassessment component is the same
Feedback on assessment

Feedback will be given on the assignment for each group and on the exam collectively. Further feedback wil be provided via my.wbs discussion forum in response to student queries.

Past exam papers for IB9HP

Courses

This module is Optional for:

  • Year 4 of USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics

This module is Option list C for:

  • Year 4 of USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics
  • Year 5 of USTA-G301 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics (with Intercalated