Professional course Big Data

Entry year
Course code
Professional/Short Course
School of Computing and Creative Technologies
twenty sessions, scheduled over twenty-four weeks
Through weekly lectures and tutorial sessions
Course Director
Dr Kamran Munir

Page last updated 24 April 2024


This course can count towards one of our postgraduate qualifications within our Information Management and Information Technology Awards

Accreditations and partnerships:

A key first step into the world of Big Data is to understand what it is, why it is different and how it is best managed. This module will introduce Big Data concepts and applications and compare traditional (SQL) to alternative (NoSQL) approaches to data storage and retrieval.  In addition to key concepts of data integrity and quality, you will have the opportunity to gain hands-on experience with big data tools.

"The course is put together in such a way as to make it very interesting and informative with a good mix of lectures and practical work. I would recommend it to anyone working in data storage and retrieval or anyone who wants to learn about new up and coming data technologies."

John Breslin, Senior Software Engineer

Entry requirements

Participants are expected to have a first degree at 2.2 level or above (or equivalent), or alternatively have industrial experience.

If you are a non-UK student you will need to show your passport on entry to the UK. Please check your eligibility to visit and study in the UK here. If you are a non-Irish EU national currently resident in Ireland please contact us directly for further advice.

If English is not your country's first language, you will be required to provide evidence to show you meet the UK Border Agency and the University's minimum English Language requirements. Further details are available on our English Language Requirements webpage

We strongly recommend that you speak to the course tutor prior to the course if you are unsure about your suitability to complete the assessment.

Careers / Further study

This module can be taken as a standalone module, or used to build up credit towards a named postgraduate qualification (PG Certificate, PG Diploma or Masters) within our Information Management and Information Technology awards



This module will cover the following topic areas:

Data Storage and Retrieval

  • Importance of data for business.
  • Understand the difference between data, information and knowledge.
  • Traditional ways to store and retrieve data.
  • Big Data challenges and opportunities.

Introduction to Big Data

  • Defining Big Data: Sources of Big Data; The four dimensions of Big Data: Volume, velocity, variety, veracity; Introducing storage and MapReduce.
  • Business application of Big Data: Big Data applications/examples in business;Delivering business benefit from Big Data; Establishing the business importance of Big Data.
  • Addressing the challenge of extracting useful data/knowledge.
  • Integrating Big Data with traditional data.

SQL Databases vs. NoSQL Databases

  • Understand the growing amounts of data.
  • The relational database management systems (RDBMS).
  • Capabilities of traditional RDBMSs.
  • Overview of Structured Query Languages (e.g. SQL).
  • Introduction to NoSQL databases.
  • Understanding the difference between a relational DBMS and a NoSQL database.
  • Identifying the need to employ a NoSQL DB.

Storing Big Data

  • Analysing data characteristics: Selecting data sources for analysis.
  • Introduction of selected Big Data stores from the following list: Hadoop, Cassandra, Amazon S3, BigTable, etc.

Achieving Data Quality

  • Introduction to data quality.
  • Why is data quality a business problem?
  • Problems when data is not "fit for purpose".
  • Preparing data.
  • Ways to improve data quality.
  • Understand ETL - Extract, Transform, Load procedures to improve Data Quality.

Knowledge-based Information Retrieval

  • Introduction to knowledge-based information retrieval.
  • Use for ontologies for knowledge modelling.
  • Learn how to build an ontology to link knowledge with data.
  • Using ontologies for information retrieval - case study.
  • Machine learning for knowledge acquisition: Introduction to machine learning and pattern recognition; Capabilities of different modelling, analysis and algorithmic techniques.

Big Data and Cloud Computing (technology, challenges and trends)

  • Cost of storing Big Data.
  • Is cloud computing a solution?
  • Issues: Privacy and trust.
  • Future of Big Data and cloud computing.
  • Future research trends in Big Data.

Learning and Teaching

The module is delivered through weekly lectures and tutorial sessions, which take place on consecutive weeks.

Each lecture will direct the course and introduce the new ideas and skills required. Then small group tutorial sessions will enable each student to carry out the study and research exercises described in the associated work-sheet under the guidance of a Tutor.

The teaching material is available from Blackboard (our online learning environment).

A course text is also recommended.

Study time

This module (course) will involve 2 hours direct contact time per week for one semester equally divided between lecture and tutorial sessions.

A 15 credit module, like this, is expected to take 150 hours to complete:

  • 24 hrs contact time through lectures and face to face discussion
  • 30 hrs coursework preparation
  • 86 hrs assimilation and development of knowledge
  • 10 hrs exam preparation


The module will be assessed through a written report and an oral assessment (presentation/viva).

For more details, see our full glossary of assessment terms.


Professional accreditation

This module is accredited by the Chartered Institute for Library, Information and Knowledge Professionals.

Study facilities

The University has excellent facilities, accessible to all students, as required; however, it is expected that much of the work will be carried out within the work environment.

Find out more about the facilities and resources UWE has to offer.

Get a feel for the Computer Science and Creative Technologies facilities we have on offer here from wherever you are.

Prices and dates

Supplementary fee information

Course dates

This course is planned to run again in 2025. Course dates, updated fees and online booking forms will be published here in the summer of 2024. Please complete our online enquiry form below to be notified once these details are made available.

Cohort February 2025TimeLocation
Twenty sessions, scheduled over twenty-four weeksTBCFrenchay Campus


Course fees

All prices are VAT exempt


CohortFebruary 2025
UK student£792.00*
International student£1,333.00*


*Fees displayed are based on 2023/24 entry and are an indication only. Please note there might be a small increase for 2024/25. Please complete our online enquiry form below to be notified once these details are made available. 

For information on fees, managing your money and determining your fee status, please go to our fees and funding pages.

Course location

UWE Bristol, Frenchay Campus, Coldharbour Lane, Bristol BS16 1QY

How to find UWE Bristol

How to apply

How to apply

This course is planned to run again in 2025. Course dates, updated fees and online booking forms will be published here in the summer of 2024. Please complete our online enquiry form below to be notified once these details are made available.

As this module carries university accreditation, once you have submitted your online booking form, you will be required to provide the following supporting information for Tutor to be able to review and formally accept your application as required by the university:

  • An up-to-date copy of your Curriculum Vitae (including contact details of a work or academic reference)
  • A brief personal statement to support your application
  • A copy of your highest qualification certificate and transcript of modules studied
  • A copy of photographic proof of ID (i.e. driver's licence/passport). For non UK students, this must be a copy of your passport
February 2025Enquire Now

For further information

  • Email: Please contact us using the online enquiry form link above.
  • Telephone: +44 (0)117 32 81043 (option 1, then option 3)