Interview - Cuurios
We caught up with Gaëtan and Leen last month over coffee and chatted about both where they are today and where they are headed in the foreseeable future.
Can you give us a little background on your interest and your background in Data Science?
Leen: I studied Mechanical Engineering and during my Master’s where I specialized in the field of Man Machine Interaction. The key motivating factor in my career has always been to support people with software solutions that give them the right information at the right time to make the best decision possible. I have since learned that Data Science techniques can be of great value to translate data to valuable information.
Gaëtan: I have a degree in Computer Science/Telecommunication, as well as considerable experience in the field of IT and software. I am deeply convinced that technology does not live in and of itself; the value of IT can be measured in its use scenarios: supporting decisions making, monitoring and managing one’s business operations. As my career develops, I have tried to practice what I preach: analyzing, designing and developing solutions for specific business challenges. Over the last few years, I have developed a keen interest in AI and Data Science, which provides business with a radically different paradigm for leveraging software engineering and information management.
What is the context and the objectives of your current work?
The key here is the importance of context. In our experience, most of the data science projects we come across are more data-centric than focused on use cases: Data by itself doesn’t have much value until its used to explore, to test, and to learn from real-live challenges and opportunities.
Unfortunately, most data science projects today seem to follow the same script: “Here is all our data, could you please perform your magic data science trick?” Too rarely Is the question asked, “What is the problem we are facing, could our data help us solve that puzzle?”
Actions should be the inherent outcome of your data pipeline, in other words use your data to incite real world changes. Our philosophy is to keep Data Science simple by developing use cases that add value right away. If you do not transform your data into actions, great potential remains untouched!
Examples of our own work that illustrate this vision include :
We believe that only by providing concrete, tangible applications can we deliver tangible value to the business and make data an integral part of our customer's daily operations. As such we design custom software solutions to address our customers' challenges and opportunities.
What opportunities do you see for Data Science in your field and market?
Our customers (and prospects) are large industrial corporations that have a large stock of proprietary that they have gathered over the years, usually accessible through either data warehouse or a data lake.
Despite this potential gold mine, they struggle to find the people, time and tools to exploit the data and transform it into relevant operational insights and actions. Moreover, most customers of our customers haven’t captured, or created, the metadata needed to interpret the massive amount of data at their disposition and apply Data Science to its fullest.
This context is usually to be found in the expertise of operators and domain experts - it is difficult to build a coherent picture without the support of a software solution.
A case in point would be one of our current clients, a large Oil & Gas corporation operating in the North Sea. We are enriching the value of their data by creating, managing actionable insights using data from their own operational database, creating an integrated data / actions platform.
In this issue :
This Newsletter has been created specifically for the BAI community to foster conversation around the use of analytics in improving business decision-making.
Interested in our March Newsletter? It can be found here.