![](\"\/wp-content\/uploads\/2018\/11\/coale4.png\")
<\/p>\n<\/p>\n
Big Data LDN<\/a> is right around the corner and this year\u2019s event (November 13-14 in London) boasts an impressive roster of speakers including big data visionaries, experts, and real-world data pros sharing insight and tips on how to build dynamic, data-driven enterprises. One of those speakers is Gordon Coale<\/a> and he\u2019s presenting a strategy session on Carlson Wagonlit\u2019s<\/a> \u201cBig Data Journey into the Cloud.\u201d We interviewed Gordon to talk about his role, his upcoming presentation, and what he hopes to see more (and less of) at Big Data LDN.<\/p>\n Technically, I\u2019m a senior director of analytics but I tend to call myself a data professional. The main reason being that I\u2019ve held so many different roles in the data arena that one label isn\u2019t particularly useful anymore. I\u2019ve spent quite a bit of time on architecture and held various architecture roles, each with a data focus. I\u2019ve also spent time as a data scientist, data consultant, and built reporting and analytics systems so I\u2019ve found that the term \u201cdata professional\u201d is one that best sums up my career and experience.<\/p>\n It comes down to pleasing my users and my clients. I still love getting my hands dirty playing with data \u2013 whether that\u2019s as an architect, data scientist, analyst, or scoping an entire program of work \u2013 but the kick for me is giving my clients and customers new insights into their own data and having them discover new things more easily.<\/p>\n There are two obvious ones. The first is the whole big data revolution. It\u2019s interesting to see how that was painted in the hype versus how it\u2019s played out.<\/p>\n The second change is the meteoric rise of the data scientist. That\u2019s an interesting label \u2013 data scientist. It\u2019s not a role that\u2019s new or was formed out of whole cloth five years ago because as a discipline it was always there. What\u2019s different is the way the role has coalesced around data science and big data toolsets and into an industry discipline rather than a niche. The role has obviously ridden the wave of the hype cycle as these things go as there are huge amounts of funding currently being put into data science projects and picking up data science resources, which gives our business users another, different technology capability and viewpoint to draw on.<\/p>\n The data science title has been a fascinating rebranding. You have quants, analysts, actuaries and some of the smartest ones I know don\u2019t care about titles and others are so happy to append a data scientist title. What are your thoughts on the data science title?<\/strong><\/span><\/p>\n I agree with you. Some people love the title because it\u2019s an easy label and brings with it a fairly well-formed idea of what someone does, even if the reality is there\u2019s a very wide range of skills and mindsets within the role. It ranges from the data analyst level to hard core machine learning engineers or data engineers. It all depends on who\u2019s recruiting and who\u2019s describing their job.<\/p>\n I\u2019ll be talking about the kind of Big Data journey that Carlson Wagonlit Travel<\/a> has been on for the last 18-20 months. We were late getting properly involved in big data beyond putting more than a toe in the water and some proof of concepts (POCs) that were going on in different divisions. There was a real inflection point about two years ago when we decided that the initial wave of excitement around Big Data had died out and some of the pragmatic benefits were starting to show. That\u2019s when it made sense for us to externally engage with the more mature products and the capabilities at that point. From an internal perspective, that\u2019s also when we started taking a hard look at our point solutions and point implementations and bringing them together for the benefit of the entire company, not just individual teams or departments.<\/p>\n There are a few go-to vendors like Cloudera and Cazena<\/a> that I always make a point of seeing, along with some of the other companies and people I\u2019ve had relationships with through many different roles. One of the nice things about working with Cazena is that we get wide insight into what\u2019s happening in the market. Then I like to take time to look at some of the newer kids on the block to see what they\u2019re doing and their interesting value proposition.<\/p>\nWhat is your role at Carlson Wagonlit Travel?<\/strong><\/span>
\n <\/h5>\nOf all those data-related roles, which is your favorite? What do you most like to do?<\/strong><\/span>
\n <\/h5>\nOver last five years, what have been the most interesting changes in data and analytics<\/strong>?<\/span>
\n <\/h5>\nCan you share what you\u2019ll talk about at Big Data LDN?<\/strong><\/span>
\n <\/h5>\nWhen you go to a large event like Big Data LDN, what\u2019s your strategy for taking in all the different vendors and talks? Do you have a certain agenda in mind or how do you navigate those shows?<\/strong><\/span>
\n <\/h5>\n