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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…

How Will Automation Tools Change Data Science?

By dotData

Data science is now a major area of technology investment, given its impact on: customer experience,revenue,operations,supply chain,risk management, andmultiple other business functions. Data science enables a data-centric decision-making process for organizations.  It is accelerating digital transformation and AI initiatives.  According to Gartner, Inc. only 4 percent of CIOs have implemented AI, and only 46 percent have plans to do so.While investments continue to grow, many enterprises find it increasingly challenging to implement and accelerate data science practices.  This article provides an overview of recent trends in machine learning and data science automation tools.  It also  addresses how those tools will change data science. Read the full article "How Will Automation Tools Change Data Science" on KDnuggets, featuring Dr. Ryohei Fujimaki, CEO and founder of dotData. Related Articles