What will I learn on this module?
This module gives you a deep understanding of the concepts, theories and foundations of Big Data, and provides you with the opportunity to develop the skills to manage massive and complex data sets – as well as to infer knowledge from data - using industry standard platforms and tools. Big data analytics is the use of advanced analytic techniques on very large, diverse data sets that might include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes. The module therefore includes an introduction to the specific nature and requirements of Big Data analytics, and to emerging trends and use cases where Big Data outperforms traditional data warehouse approaches. It will include an understanding – and practical use of- contemporary open-source tools such as R, Hadoop, HDFS, MapReduce, Yarn, Spark, Storm, and Hive. The module will also cover concepts of critical data studies and provide a forum for you to investigate the continuing ethical, sustainable, environmental and societal implications of Big Data. For example, sustainable practices in Big Data analysis pipeline optimization and incorporating energy-efficient design ideas. Ethical issues around how Big Data can be used will be explored.
How will I learn on this module?
You will learn through lectures, workshops, and independent learning. The lectures will cover theories and concepts around Big Data that will enable you to tackle a series of guided practical exercises. Some lectures and workshops will be dedicated to discussing critical data studies topics and will feature guest lectures on this subject. You will work on practical exercises during workshops in Northumbria’s CIS building computer labs, which are fully equipped with the latest industry-standard software.
How will I be supported academically on this module?
You will be supported by lecturers during the timetabled sessions, when you will receive feedback on your work. The University’s eLearning Portal offers remote access to all lecture and seminar materials to reinforce your learning. In addition, the university library offers support for all students through the provision of digital reading lists. Specific resources to be provided include curated lists of state-of-the-art research publications, and appropriate Big Data software, platforms, and services with which to build your own applications.
What will I be expected to read on this module?
All modules at Northumbria include a range of reading materials that students are expected to engage with. Online reading lists (provided after enrolment) give you access to your reading material for your modules. The Library works in partnership with your module tutors to ensure you have access to the material that you need.
What will I be expected to achieve?
Knowledge & Understanding:
MLO1 – Show comprehensive understanding of the Big Data system architecture, with graph and/or statistical modelling, the principles of organisation, validation, transformation and analysis of large volumes of data on specialised platforms.
MLO2 - Demonstrate a comprehensive understanding of the advantages and limitations of Big Data technologies, including predictive analytics and build the confidence to interpret data as insights to drive organisational success with adequate risk management approaches.
Intellectual / Professional skills & abilities:
MLO3 - Demonstrate competence in advanced tools for data collection, data cleaning and integration and parallel data mining.
MLO4 Participate in informed discussion around the legal, social, environmental, security, risk, ethical and professional framework for developing data-intensive systems.
Personal Values Attributes
MLO5 – Demonstrate advanced literature search and synthesis capabilities.
How will I be assessed?
There is a single assessment for this module. You will develop an application that shows your competence in using advanced tools for data collection, data cleaning and integration of parallel data mining and data insights to drive organisational success. You will document this application in a 4,000 word, which should adhere to the structure of a scholarly research article, detailing the methodology, design decisions, performance of the designed system/pipeline, and an analysis of the results. It should also include a critical reflection on the project's research questions and the development process, offering insights into potential improvements or optimisations for future efforts. Additionally, the report should address any legal, environmental, societal and ethical considerations related to the project, outlining measures taken to address potential security risks that are specific to Big Data. The reports should also present a detailed risk analysis, identifying project-associated risks and the strategies employed to mitigate them.
Pre-requisite(s)
N/A
Co-requisite(s)
N/A
Module abstract
This module is focussed on understanding the storage, manipulation and analysis of Big Data: that is data that is high in volume, is captured at high velocity and contains high variety (in terms of structured and unstructured parts). You will investigate the tools and techniques both for storage of this data, such as distributed databases and filesystems, and for processing this data, such as Apache Hadoop and Apache Spark. You will also gain an appreciation of the social implications of the continued rapid development of Big Data tools and applications. All these topics and methods have become essential concepts and approaches that can be used by data scientists in many sectors including retail, economics, finance, media and healthcare.
Course info
UCAS Code G411
Credits 20
Level of Study Undergraduate
Mode of Study 3 years Full Time or 4 years with a placement (sandwich)/study abroad
Department Computer and Information Sciences
Location City Campus, Northumbria University
City Newcastle
Start September 2025
All information is accurate at the time of sharing.
Full time Courses are primarily delivered via on-campus face to face learning but could include elements of online learning. Most courses run as planned and as promoted on our website and via our marketing materials, but if there are any substantial changes (as determined by the Competition and Markets Authority) to a course or there is the potential that course may be withdrawn, we will notify all affected applicants as soon as possible with advice and guidance regarding their options. It is also important to be aware that optional modules listed on course pages may be subject to change depending on uptake numbers each year.
Contact time is subject to increase or decrease in line with possible restrictions imposed by the government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors if this is deemed necessary in future.
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