So, at a high level, some future version of this software will show intuitive visualizations of learned models of the data? Or currently, at a lower level, it s

So, at a high level, some future version of this software will show intuitive visualizations of learned models of the data? Or currently, at a lower level, it seems to be implementations of standard machine algorithms with a Python API to use them. There seems to be an emphasis on efficiency, although I don't think that most freely available machine learning libraries are fundamentally poorly implemented. One problem with these libraries is that documentation can sometimes be scarce. Another problem, for the 0.01% of companies which actually have "big data", is that they might not scale, whatever that means. Regardless of the library used, one of the bigger problems may be that machine learning, if it's worth it at all, is inherently fickle and tricky. To make an overly broad conjecture: if an externally provided machine learning solution works well, either your data didn't require that much domain knowledge to understand (it was "obvious") or some external/outsourced firm has a deeper understanding of your data than you do. More of the former type of analysis might not necessarily be a bad thing, though.