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AutoML: How Do You Measure Return On Investment?

By Walter Paliska

So your company has decided to invest in an Automated Machine Learning (AutoML) platform. Excellent - AutoML promises that it can help accelerate and automate much of your data science process. At first blush, the return on investment (ROI) for your technology purchase would seem simple: Measure how many data science projects your team could produce on average before your platform purchase, and then measure again afterward. If your results are anything like what our clients have seen, you will likely measure ROI in terms of time: many of our clients are finding that they can deliver data science projects 10X to as much as 32X faster than they could manually. While those numbers are high, however, there are other even more powerful means of measuring ROI that will be even more meaningful and valuable to your business. Leaders should think beyond cost savings and look at developing sustainable competitive…

Ryohei Fujimaki at PAWCon 2019

By dotData

Ryohei Fujimaki, PhD and CEO of dotData, shares more about the data science platform at Predictive Analytics World 2019 in Las Vegas.https://twitter.com/thebloorgroup/status/1141688670421954560 Related Articles