| Unit name | Large-Scale Data Engineering for Business |
|---|---|
| Unit code | SEMTM0039 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Dr. Rochat |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Engineering Mathematics and Technology |
| Faculty | Faculty of Engineering |
Why is this unit important?
This unit aims to give a comprehensive overview of elastically scalable and remotely-accessed "cloud" computing services such as those offered by Amazon, Google, and Microsoft, and associated technologies for dealing with very-large-scale bodies of data.
Cloud computing has developed rapidly and is being adopted in a wide variety of industries. In today’s world, every data scientist working with “Big Data” needs a thorough grounding in cloud computing, X-as-a-service, and the technologies and practices covered in this unit.
How does this unit fit into your programme of study
Large-Scale Data Engineering is a core unit in the Data Science MSc and related degrees. It covers essential content on working with very-large-scale datasets that will be essential to you in the project work that follows throughout the rest of the degree.
This version of the unit is the specialised form for you taking the Data Science for Business MSc. The teaching will mostly be the same as the teaching for you on the Data Science MSc, but the examples used in classes and the exercises used in assessments may focus on applications in business.
An overview of content
The unit commences with discussion of the economics that have driven the rapid development and adoption of cloud computing in a variety of industries; it then explores the provisioning of cloud services moving from Infrastructure-as-a-Sfervice (IaaS), through Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS), and "serverless" Functions-as-a-Service (FaaS). The open-source Hadoop "ecosystem" cloud service projects is introduced, and various cloud data-storage and data-processing technologies are surveyed, with evaluation of their strengths and weaknesses. The unit closes with an overview of best practices in the use and management of Big Data.
How will students, personally, be different as a result of the unit
The unit will equip you with necessary skills in cloud computing and big data processing. You will understand key concepts and philosophy of cloud computing. You will be able to use cloud and big data processing technologies. Finally, You will be able to design the architecture and deploy real-world applications in the cloud.
Learning outcomes
On successful completion of the unit, you will be able to:
1. Explain the economic factors and economies of scale that have driven the development of cloud computing;
2. Compare and appropriately select among the various cloud computing services offered by major providers such as Amazon, Google and Microsoft, and have direct experience of initiating, running and managing, and closing remotely accessed computational resources via X-as-a-Service access models;
3. Demonstrate competence as a practitioner of cloud computing architecture with reference to fundamental concepts such as availability, reliability, scalability, elasticity, security, cost effectiveness and automation;
4. Demonstrate the combination and use of cloud computing technologies such as in-memory compute and stream-processing in high-performance and high-throughput applications;
5. Apply effective methods to store, manage, process and secure data at very large scale (‘Big Data’).
Teaching will be delivered through a combination of synchronous and asynchronous sessions, including lectures, group work, practical activities and self-directed exercises.
Tasks which help you learn and prepare you for summative tasks (formative):
You are allocated a two-hour tutorial session per week. The tasks assigned directly and indirectly equip you for the summative assessments. You will receive the feedback from the teaching team in the tutorials.
Tasks which count towards your unit mark (summative):
Coursework (100%) on implementing and optimising an effective cloud architecture for an existing data processing application. This will assess all ILOs.
When assessment does not go to plan:
Re-assessment takes the same form as the original summative assessment.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. SEMTM0039).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
