By KLaker on Jan 17, 2014
We have released yet another great video customer video, this time with Stubhub.
Many customers are still pulling data out of their data warehouse and shipping it to specialised processing engines so they can mine their data, run spatial analytics and/or built multi-dimensional cubes. The problem with this approach, as the team at Stubhub points out, is that typically when you move the data to these specialised engines you have to work with a subset of the data that is sitting in your data warehouse. When you work with a subset of data you immediately start to impose compromises on your analytical workflows. If you can't work with all your data then you can't be sure that your analytical model is as good as it could be and that could mean losing customers or missing out on additional revenue.
The other problem comes from everyone using their own favourite tool to do their analysis: how do you share your discoveries, how do you develop a high level of corporate-wide analytical skills?