Data Mining and Data Analytics go hand In hand in the world of big data. Data Mining is used to find patterns among large datasets, while Data Analytics is used to test hypothetical models on particular datasets. Over a period of time, you acquire skills that companies see as valuable to their organization. It's these skills that set you apart in the market. As you hone these skills over time, you become good at many different soft skills that accompany the technical skills. Here's where you can use a combination of these skills to articulate a compelling message that explains the differences between Data Mining and Data Analytics.

A very important question that might come from an interviewer is how much data do you analyze, and how do you manage that data without risking a security breach. Large scale big data projects use tools like Hadoop as a repository for this data. The reason I mention it is the hiring manger might ask what repository you use to store it, and what your level of confidence using this tool is.