‘Working with data is noisy and unstructured, but it has a lot of potential’
Theo Lynn, professor at DCU Business School, and researcher at the Irish Centre for Cloud Computing and Commerce. Image: Dublin City University

‘Working with data is noisy and unstructured, but it has a lot of potential’

13 Feb 2017414 Shares

When it comes to working in data, the roles most people are aware of are the big hitters – data science and data analytics. But the sector is far more varied than that.

Theo Lynn is professor of digital business at Dublin City University (DCU) Business School and researcher at the Irish Centre for Cloud Computing and Commerce. Here, he tells us about his work as a data researcher.

What is your role within Dublin City University?

Professor of digital business.

If there is such a thing, can you describe a typical day in the job?

I travel a lot, so a typical day can be very long or short, depending on where I am coming from or going to.

I primarily work on market-focused research, so most mornings involve meetings with existing or prospective client companies or partners. They nearly all have some question they want answered in the digital space, and range from start-ups to multinationals. Increasingly, they are from all sectors and are grappling with decisions around strategy, marketing performance measurement, cloud computing and risk associated with data.

Frequently, we host international visitors. For example, the IDA regularly asks us to present to prospective multinationals seeking to locate in Ireland.

The early afternoon is typically taken up with project meetings and conference calls, particularly those with EU projects. Eventually, I get around to doing some analysis and research of my own.

I don’t get to teach as much as I used to due to research commitments. I am not sure the students regret this as much I do! Nonetheless, it’s still nice to present your ideas to students and businesses from time to time. If one person gets something from a presentation, it’s a win.

What types of project do you work on?

My current research really falls into three areas: electronic word of mouth research using big data from social networks, data protection and trust, and other cloud computing research.

At DCU Business School, we have been working with firehose data from social networking sites for two to three years now, and have completed analytical studies on everything from the English Premier League to the water protests. We are particularly interested in looking at what determines influence or user engagement on a particular platform for a particular topic.

Data security and trust-related issues are the number one barrier to cloud computing adoption in Europe so, unsurprisingly, that is a major focus of our research.

The new General Data Protection Regulation enters into application in 2018 and this, combined with Brexit and the Trump administration, is causing a lot of uncertainty for Irish and international companies. We work with the cloud computing industry to help them communicate trustworthiness; identify gaps in their data security; put in place policies, processes and systems; and identify how best to prepare for and manage data breaches.

We are involved in two major EU projects – CloudLightning and RECAP – representing a research investment of more than €8m from the EU Horizon 2020 research programme. These are looking at next-generation architectures and processes for more energy-efficient cloud computing.

What skills do you use on a daily basis?

I am a firm believer in trying, where possible, to use the best evidence available to make decisions. I literally don’t trust myself, so a lot of the skills I use on a daily basis involve questioning – often vigorously – assumptions for various decisions we are exploring.

We like data. We work with social media data a lot. It’s not every researcher’s cup of tea. It’s noisy and unstructured, but with a lot of potential. Possibly a bit like me!

Every day, we use a whole raft of different skills to prepare data, visualise data and analyse data. It is different than when I was at college in the ‘90s, when the main focus was traditional statistics with an emphasis on regression. Now, we use a combination of analytical techniques including clustering, classification, text mining and network analytics to identify phenomena and generate insights. Tableau, R, Gephi, Leximancer and SPSS are just some of the tools we use in our work.

Coupled with tenacity and persistence, the ability to look at things differently is very important.

What is the hardest part of your working day?

Switching on and off is the hardest. A hypermobile life seems exciting, and it is, but it takes a toll on family life. Luckily, I have a very understanding wife and kids who have no interest in what I do at work.

Do you have any productivity tips that help you through the working day?

Escapism works for me. Walk around, and frequently. I collect science fiction and fantasy books, so reading about something totally different often helps me stimulate productivity.

When you first started this job, what were you most surprised to learn was important in the role?

Before joining DCU, I had a life as a professional start-up entrepreneur. That’s effectively all I did – set up and, ideally, sell businesses. I could make my own decisions and, if actions needed to be taken, I could take them.

Universities are very different. Academics don’t particularly work for each other – they form coalitions to make decisions and work on projects. This can be very frustrating at times, but also very rewarding over time. It takes some time to adjust to.

How has this role changed as this sector has grown and evolved?

The emergence of social media, cloud computing, mobile technologies and big data/analytics is disrupting most sectors, organisations and functions. Five years ago, cloud computing was a platform with a lot of potential. By 2019, it will represent 67pc of all enterprise computing. It is mainstreaming right now.

Consumer surveillance is now habitual. Making the right decisions based on the data generated from such surveillance is not.

Our technology is constantly evolving. Our ability to make good decisions based on outputs from this technology needs more work.

What do you enjoy most about the job?

Identifying ideas. Exploring. Testing. Learning. Discarding. Repeat.

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