Really, the goal is to use the right tool for the data analysis they're doing. 90% of the time, that's Excel; they're looking at reports that can easily be piv

Really, the goal is to use the right tool for the data analysis they're doing. 90% of the time, that's Excel; they're looking at reports that can easily be pivot tabled or VLOOKUP'd to get what they need, or use the strengths of the UI and auto-updating to get the formulas they want working in an easily tweakable fashion. For those cases, things like R, SQL or Python can be overkill, especially if you spend more time preparing the data format than it would take to use Excel, let alone analyze the data. However, 10% of the time, they're pushing Excel beyond the limits of what it can handle and wasting time as a result, spending an hour doing massive VLOOKUPs between two huge spreadsheets looking for an answer that SQL can answer in a heartbeat. Those are the use cases I want to solve for; where the advantages of statistical software, scripting languages and relational databases overtake the powerful and convenient simplicity of Excel.