One of the (many) particularities of data mining is to be at the intersection of several fields. One can mention statistics, machine learning and databases. Skills in these 3 domains are thus necessary (but not sufficient) to be an efficient data miner. One of the most important (if not the most important) category of skills for a data miner is communication.
Among the communication category, one can gather skills such as listening, presenting and vulgarizing. The importance of such skills is even more true in the recent role of data scientist. The starting phase of the CRISP-DM framework is business understanding. To correctly apprehend the business, the data miner needs to have listening skills. Reading documentation won’t be enough, you need to listen to domain experts.
The ending phase of a data mining project is (usually) the deployment. The success of this phase mostly depends on how the developers understand the data mining project and its goals. It’s the role of the data miner to present the project, its results and specifications for the deployment. Good presentation skills are needed in order to correctly explain the project (through vulgarization when needed).
What do you think about the need of these communication skills? Do you think there are other soft skills needed for a data miner?Fostering a data-driven culture (The Economist): Discuss the power of data among the company and the meaning of Big Data for experts. Based on a study of 530 senior executives. •… Continue reading...Continue reading...Agam Analytics. Stephane Zrehen from Agam Analytics started with a presentation entitled From patient stratification to client profiling. Michal Piorkowski, a former employee of… Continue reading...This short and well written book by Darrell Huff is a journey in the world of misleading statistics. The book is full of funny drawings from Irving Geis. Although not technical, the book covers several important topics. Bias, for example in polls, is detailed through several examples. The misleading word "average" is compared to terms such… Continue reading...data mining blogs and... subscribe to newsletters. Here are the top 5 data mining newsletter you should subscribe to:
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