Spark new insights and value from your data
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 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.
- Strategic business challenge
- Vanguard methodology & technologies
Experimental R&D platform
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 projects 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 six week exploratory student project
- Rapid, tangible results
- Five-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 Data Observatory (secondary research project)
We believe that organisations of the future will be radically reconstituted by breakthroughs in data science and business analytics, bringing fundamental changes to how companies manage people, operations, and marketing.
We are interested in high-impact Data Spark projects which fit this profile, if you are interested in our scheme then get in touch.
"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."