a man sat looking at a computer

Professional course

Big Data

About this course

Course code:
Z41000093
Applications:
University
Level:
Professional/Short Course
Department:
Computer Science and Creative Technologies
Campus:
Frenchay
Duration:
Twelve two-hour sessions, scheduled over twelve continuous Wednesdays
Delivery:
Through weekly lectures and tutorial sessions
Programme leader:
Dr Kamran Munir
Key fact:
This course can count towards one of our postgraduate qualifications within our Information Management and Information Technology Awards

Page last updated 26 September 2019

Introduction

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.

Entry requirements

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

Overseas students need to have, in advance of application, either a valid student visa or evidence of residency status in the UK.

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

Structure

Content

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

Each 15 credit course (module) is expected to take 150 hours to complete:

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

Assessment

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.

Features

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

 
CohortJanuary 2020
UK/EU Participants£625
International Participants£1,083
Application DeadlineMonday 13 January 2020*

*Please note parking and refreshments are not included as part of your course fee

Course dates

CohortStart DateSession Time
January 2020Wednesday 22 January 2020*12:00-14:00

*then every Wednesday until 01 April 2020; and 22 April 2020

Location

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

How to apply

How to apply

As this module carries university accreditation, once you have submitted your online booking form, you will be required to provide the following supporting information to the administration team 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

Overseas participants will be required to provide evidence of visa status once accepted onto the course, before they can be fully registered and attend.

Cohort  
January 2020Book NowEnquire Now

For further information

  • Email: For all queries regarding the administration aspects of registration, i.e. dates, fees, etc. please contact us using the online enquiry form link or telephone number below. For any questions in relation to the course, i.e. content, suitability, assessments, etc. please contact the Programme Leader, Dr Kamran Munir.
  • Telephone: +44 (0)117 32 86927

Back to top