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Professional course

Big Data

About this course

Course code:
Professional/Short Course
Computer Science and Creative Technologies
Twelve two hour sessions scheduled over a period of 12 weeks
Course director:
Dr Kamran Munir

Page last updated 28 February 2019


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.

Highly recommended

"This is a relatively new and innovative subject and the course was put together in such a way as to make it very interesting and informative with a good mix of lectures and practical work.

The lecturers were very knowledgeable in their subject areas and were well equipped to explain and discuss new concepts in computing and data storage.

I would recommend this course 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 and Big Data student 2016

Entry requirements

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


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


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.

Prices and dates

Supplementary fee information

CohortUK/EU ParticipantsInternational Participants
January 2019£583£1,042

Course dates

This course will next run in our 2019-20 academic year. To be kept up-to-date with our course dates please complete the enquiry form below.


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

How to find UWE Bristol

How to apply

How to apply

On acceptance onto the module, you will be registered onto our student system to give you access to university resources, including the library and your module BlackBoard site where course materials and pre-reading/work will be posted.

January 2020Enquire Now

For further information

  • Email: For all queries, please complete the online enquiry form above.
  • Telephone: +44 (0)117 32 86927

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