Imperial Business Analtyics
It’s not how much data you have that matters, it’s how you use it.
Leveraging some of the world’s best academics, industry experts and technologies, the Data Spark scheme provides an agile and innovative research and development platform that enables business leaders to experiment, test new ideas, and create PoC’s.
Data Spark tackles real life problems faced by business decision makers to drive fresh insights into their data and business.
The Data Spark programme is a great initiative, bringing academics closer to real-world data-related problems that industry regularly faces. World-class expertise in the latest analytical techniques from Imperial College is fused with business insight from KPMG and means that during the Data Spark process participants design solutions that are both cutting edge and practical. The six-week programme means it is challenging for the students and there can be a steep learning curve, but an experience worthwhile, giving a taste of how their skills can be developed and applied.Alex Healing,Chief Researcher of Visual Analytics, BT Research
The insights our team derived from analysing the big data made available to us were extremely surprising. In such a global financial organisation, one would assume that gender biases would not play any role, however we found evidence of some underlying unconscious bias. What was reassuring about this project was that it was clear from the very start the organisation was forward-thinking and seeking to actively curb any such biases. We were pleased to be able to provide valuable insights to the company which will help to contribute to their gender equality strategyDevanshi Shah,FT MBA 2017
As a student, it’s rare to come across an opportunity to work closely with top executives to produce first-hand research and strategic recommendations for a global business. I am very glad that I took part in Data Spark, as constant challenges along the way have rewarded me a higher level of problem-solving skills and analytical thinking. I have truly progressed with my team.Chu Wang,MSc Management 2017
The Data Spark programme was the highlight of my year at Imperial; a fantastic opportunity to work on an analytical project from start to finish, experience real-world data issues, apply the skills I gained throughout my course and deliver valuable business insights.George Pastakas,MSc Business Analytics, 2017
How does it work?
For business leaders, making data driven decisions is critical but sometimes it’s hard to spot the opportunities in the data and developing trends that are going to make the difference.
That’s why we have developed The Data Spark.
An innovative student placement scheme designed to uncover fresh insights into your data, whilst providing an opportunity for our very best students to apply the methodology and skills developed at Imperial College London to real-world business problems. All under the close mentorship of world-leading academics.
Your data, your challenge, our expertise
- Innovative 6 week exploratory student project
- Rapid, tangible results
- Volunteer 5-person student team
- Academic mentor with speciality in the problem domain
- Supported, targeted recruitment
- Projects designed to support longer-term research
- Visualise your data in the KPMG Data Observatory (secondary research project)
The students did an impressive job of exactly what we see from really good analytics projects. On the one hand, it’s powerful to have beliefs and hunches confirmed by data, which they did. Even better, it’s great when you also see creative combinations of data to produce proxies of things you don’t have measures for, which they also did. For example, the students were able to determine if managers were likely working outside their country of origin, and that in some circumstances this may be a group that would benefit from additional support.Robert Carlyle,Senior Director, RBC
Data Spark student applications
The Data Spark scheme will be open for Imperial College London students to apply for the 2019/20 scheme from mid-October 2019.