By studying a big data course at postgraduate level, you'll be well positioned to enter a profession at the forefront of technology, developing the skills required to interpret data and inform key business decisions
What is big data?
Big data is a term that relates to how organisations manage the large volume of data they face on a daily basis.
By analysing the data for possible patterns and correlations, the findings can be used to provide greater insights into the business. This, in turn, leads to better decision-making and the development of more informed strategies.
What is AI?
AI is the simulation of human intelligence processes by machines, especially computer systems.
Today, AI is comprised of multiple fields, each pertaining to a different area of AI focus - machine learning, natural language processing, computer vision, cognitive computing, robotics, deep learning, automation, strong AI and much more.
The application of AI-based technology has become common in the business space - and has penetrated the consumer space as well.
How is big data utilised?
Private and public sector organisations have access to vast amounts of data they collect from users, customers and suppliers - much more than ever before.
Therefore, big data is about sorting, understanding and gaining knowledge from this mass of facts and figures. It can then be used to find cost savings and improve products and services.
In addition, all of this data - which can include personal records - must be kept safe if an organisation wants to retain public trust.
Most definitions of big data emphasise the so-called 'three Vs':
- the enormous volume of data that can now be stored and analysed
- the incredible velocity with which data is gathered and must be processed
- the variety of different types of data available.
Leading analytics software provider SAS also includes:
- the complexity of today's data, which arrives from numerous sources, and the need to connect and make sense of this data across systems so it doesn't get out of control
- the variability of data flows, with daily, seasonal and particular events causing periodic peaks, making it a challenge to manage these inconsistencies.
Whether their data is collected through traditional methods, such as point-of-sale (POS) and call centre records, or digital sources - for example, tracking web behaviour and social media interactions - employers are increasingly aware of the opportunities and the risks it presents.
This means they need graduates with the right skills and qualifications to work with data both securely and effectively.
How does AI fit in?
When it comes to AI, voice-activated personal assistants such as Apple's Siri and Amazon's Alexa, represent progress in the field of natural language processing. Meanwhile, businesses are utilising machine learning algorithms to enhance business operations, improve customer experiences, automate processes and support security protocols.
In healthcare, computer vision (the ability to interpret masses of information from digital images) is helping medical professionals better detect tumours to improve cancer treatment.
More and more businesses are using AI-based solutions, such as those offered by SAS, to deal with the scale of information from big data and the need to address consumer requirements in real-time to keep pace with the competition.
Employed across retail, finance, security, marketing, manufacturing and many other sectors, AI has quickly become a 'must have' for the modern business. And yet, while AI is increasingly used across industries, we've only scratched the surface of its potential applications and capabilities.
Why study big data?
According to the most recent Dynamics of data science skills report (2019) by Burning Glass Technologies, commissioned by the Royal Society, the demand for data scientists and data engineers has tripled within five years.
Following on from this, DevSkiller's IT Skills Report 2022 revealed a 295% increase in the volume of data science-related tasks set for interview candidates by employers in 2021.
This 'explosive demand' for data science skills highlights the fact that job opportunities are available for those with the right skills and qualifications.
What roles are available in data science?
Jobs are available in all sectors because big data is used by every type of employer, from retail and banking businesses to those involved with healthcare and manufacturing. It's also harnessed by government agencies and used to implement effective education systems. This is a growing industry that's only set to get bigger.
There are many different jobs in big data, including:
Since there are currently not enough people with relevant qualifications to fill all data science roles, taking a postgraduate course in this field will ensure that you're well placed when starting your career.
What do big data courses involve?
A growing number of UK universities offer postgraduate courses in big data as they respond to the increased demand for the subject. Most are designed to lead directly to a career in data science.
You'll learn about key concepts, practices and methodologies, essential coding skills, web analytics, machine learning, advanced database skills, and how to analyse, visualise and interpret data. You'll also be trained in the use of tools such as Apache Hadoop, a software framework for storing and processing big data.
As well as taking a series of required and optional modules, to complete a big data Masters you'll usually be required to produce a major project integrating all the theory and practice you've learned throughout the year.
Which institutions offer postgraduate courses in big data?
The University of Stirling runs a number of big data and data science courses at postgraduate level, including the one-year full-time MSc Big Data, which is accredited by BSC, The Chartered Institute for IT, and can lead to various data scientist jobs.
Some institutions have partnerships with SAS and give you the chance to gain industry-standard certifications during your study. These include:
- University of Derby - MSc Big Data Analytics
- Salford University - MSc Data Science
- Sheffield Hallam University - MSc Big Data Analytics
Similarly, Queen Mary University of London's MSc Big Data Science with Machine Learning Systems is run in partnership with technology company IBM, while Heriot-Watt University's MSc Data Science is accredited by the British Computer Society.
Other courses that have a slightly different focus are available, such as the cyber security implications of big data, the role of cloud computing, or how big data impacts on business leadership.
For instance, King's College London runs an MA Big Data in Culture & Society, which looks at the subject from an arts and humanities perspective.
For a dedicated AI Masters, you could choose the MSc Artificial Intelligence on offer from:
- Cardiff University
- City, University of London
- Imperial College London
- King's College London
- Manchester Metropolitan University
- The University of Edinburgh
- University of Surrey.
Masters courses last one year if studied full time, and entry requirements typically include at least a 2:1 degree in a computing-related or other quantitative subject. However, this varies so you should always check with your chosen institution.
To find courses that suit you, search for postgraduate courses in big data.
What about online data science courses?
In addition to the university options above, a number of training providers offer online courses in data science and data analysis, with many leading to certification from industry leaders such as IBM or Microsoft:
For instance, you could complete the Introduction to Data Science Specialisation course from IBM or the Professional Certificate in Data Science from Harvard University.
Many of these courses are free, although you may still have to pay to get a verified certificate.
Other specialist e-learning providers such as DataCamp also run accredited data analysis courses focusing on SQL, Python and R, enabling you to develop technical skills and advance your career.