All around us we are surrounded by information and data. In fact — there is so much information bombarding us each day that there’s even information about recovering from information overload. With terms like Big Data, Data Scientist, Machine Learning, and others dominating every corporate conversation its not hard to see that sometimes there might be slip-ups in analysis or understanding of this information. This can cause issues like what we have seen with recent interpretation of Uber data.
As a current social research lead at Adobe and a former Godfather of the Adobe Digital Index team that produced thought leadership for outlets like Wall Street Journal, CNBC, New York Times, and Forbes I decided I would put together a short list of ways to ensure the best insights are created from the mountains of data that we now have access to.
- Have an intimate knowledge of the data you analyze – When I first started analyzing Adobe marketing cloud data, I attended every training possible about the products that were producing the data. I talked with engineers, sales people, even customers to understand better how they used the products and implemented them. This knowledge helped me to know what data was available to analyze, how to identify if data was not correct or needed cleaning, and most importantly create a working relationship with the guardians of the internal data.
- Learn statistics – You don’t need to be able to create complex models, write code, use R, or be able to predict the next economic down fall to be a great analyst. A basis understanding of means, averages, outliers, histograms, standard deviations, and other statistical terms will go a long way in helping you to create a true trend free of outliers from a large data set. You can go the formal route through online degree like a masters in stats from my alma matter Utah or through free routes on Coursera.
- Be curious – Adobe has an unmatched data set with the marketing cloud, so I have a great playground to learn about trends across all industries. However, I was only able to succeed in analysis because of my curiosity for knowledge through data. Over the last four years — among other things — I have predicted movie success with social buzz, analyzed Brazilian sentiment around the World Cup, shown that broadcasters still rule the content game in social, found what were the hot knew items in IoT, and which Super Bowl ad was the best based on six points of social data. These ideas were all cultivated by my curiosity for proving points with data.
- Always question results – Even after cleaning, averaging, and removing outliers you should still always question your results. Make sure it passes the sniff test and compare to other historical results if available. Also, if possible, ask colleagues to do a peer review of your work to ensure that you feel confident and comfortable with what you share internally or externally.
- Find your passion – Social data is my passion and it took me about two years to figure that out. I was able to analyze other data just fine, but social really got me excited. Everyone will be different and it can take time to find what you truly enjoy. Once you find that passion follow it and examine it as much as you can. You will find that when you are working on something you have passion for that it will be the most natural path to success in being an analyst.
This list is by no means comprehensive, but can at least provide a glimpse into ways to produce meaningful insights from data. Curiosity and passion are the too that really can’t be taught. You will have to look inside yourself to get an understanding of what truly drives you to finding results in data.
Commentary on social sites doesn’t necessarily reflect that of the company that I work for.