For Machine Learning, Data Comes First

CEO Robbie Allen recently spoke about the importance of data strategy at Adobe’s Think Tank on The Future of AI in the Enterprise.

“People hear about artificial intelligence and all this crazy stuff that it’s doing and so they think that it’s going to be this magical solution that solves all of their problems,” he said.

“In most cases, in my experience, it’s better to walk before you can run when it comes to this, especially if you’ve never done a machine learning style project before which requires a significant amount of data. You first have to to get your data strategy in place first before you can have an AI strategy.”

Later, Robbie spoke about a common data issue many enterprises may not be expecting: the high cost of getting data out of their systems.

“It’s likely that companies will spend just as much money on getting data out of their systems as they did to implement the systems to begin with,” he said.

“What I mean by that are ERPs, CRMs, all their databases. To get the data out of it in a format that’s useful for machine learning algorithms and other things is a nontrivial task.”

“And it turns out to be, in most cases, the long pole in the tent. That is, the hardest aspect of actually implementing a project is just to get the data. So that’s why we were talking about before, data strategy, when do you get it – it’s going to be difficult to do much in the space in the enterprise unless you have access to data in a format that makes it available to somebody to use in terms of implementing algorithms.”


Share this post