About this course
- Course code:
- Professional/Short Course
- Computer Science and Creative Technologies
- Twelve two-hour sessions scheduled over a 12 week period
- Through weekly lectures and tutorial sessions
- Programme leader:
- Dr Paul Matthews
- Key fact:
- This course can count towards one of our postgraduate qualifications within our Information Management and Information Technology Awards
Page last updated 13 August 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.
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 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 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).
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.
Supplementary fee information
|Application Deadline||Monday 13 January 2020*|
*Overseas students will need to have in advance of application, either a valid student visa or evidence of residency status in the UK.
|Cohort||Start Date||Session Time|
|January 2020||Wednesday 22 January 2020||12:00-14:00|
UWE Bristol, Frenchay Campus, Coldharbour Lane, Bristol BS16 1QY
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
|January 2020||Book Now||Enquire 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.
- Telephone: +44 (0)117 32 86927