In the Part I & Part II of this post we discussed the importance of statistics and programming skills to be an analytics professional, but we also underpinned the fact that Analytics is not all about statistics only! We also discussed the importance of communication skills and how without communicating the results effectively, it’s difficult to derive value from the analysis.
In this post we would discuss the required soft skills and how you could go about attaining the same. We would conclude this series with a discussion on hard skills in Part IV of the article.
Let’s understand this concept with a simple example; say you are trying to analyze the survivors in the unfortunate and tragic Titanic mishap. To simplify our analysis say you are provided with three variables: Name of Passengers with Title, Gender & Survivor Flag. Now someone may say that the Name variable is just an identifier variable and ignore it, and if they see that in general majority of females survived would stop the analysis there. However, another person analyzing the same data may want to see if he can extract some information from the Name variable. If the title corresponds to Doctor or Duke or Count, does it affect the probability of survival even if the person is a male or a female? Intellectual curiosity is about asking your own questions rather than only answering the asked questions. The curiosity to explore data in creative ways and extract as many features from it as possible is what separates the strongest data scientist or analytics professional from the rest.
Developing intellectual curiosity would need lots of effort from one’s side. The best way we would recommend is to start your own mini data science project or investigations; there are loads of data available for free over the net. Interested readers may look at our Datasets section where we have compiled some of the major data resources. Data science competitions like Kaggle, is another way to hone your intellectual curiosity, we’d recommend the Knowledge competitions first, and then you may start competing for the prize.
Remember, it’s all about data and data in knowledge full hands is information. To mine the data from various sources and extract the relevant information it is important that you are clear about what is the question that you are trying to answer, in other words the Business Problem. For example, to build a credit scoring model for a bank, it is important for you to understand the overall context of performing this exercise, what is the nature of business of a bank and what could be the factors that might lead a person to default his credit. Without proper knowledge of the business and the problem you might end up with a solution that was not sought after or may even lead to spurious relations. Say for example, if you conclude from your results that if a person has changed his eating habits and that are contributing to his default score to a certain extent, this would be a case of spurious relation.
The best way to develop business acumen is to put yourself into the shoes of the business manager. Don’t jump to conclusions straight away; think of the problems that a business manager may be facing, say in our case, customers defaulting on the payments. What are the implications of these problems, and what possible remedies can be done? Again, in this case the implications are loss of principal and the interest, and for remedies the bank can avoid giving credit to such customers provided they are able to identify them beforehand. Domain knowledge is something that would come with experience, but you can go through several case studies to get an idea of how business managers think.
We discussed about this in detail in the Part II of our post. It is of utmost importance for an analytics professional to present their technical findings to non-technical people like business managers. Always remember, the insights you gain from your analysis would be transformed into actions by the business managers, hence it is necessary that you present your findings in a way that are easily interpret-able by non-technical people and enable them to make effective business decisions.
You can improve on your communication skills by going through several case studies and blogs, particularly identify the technical topics and how the author has presented it in an easy to understand manner. Communication forms one of the most important pillar of Analytics Bodhi, and hence we will ensure to present however technical topic it may be in an easy to understand an interesting manner.
In this article we discussed the importance of soft skills and how to develop on them. Particularly we discussed the need for Intellectual Curiosity, Business Acumen and Communication Skills and how to work on them. We would conclude this series with the relevant hard skills in the part IV of our post.