ML is beginning to drive business impact, with automated anomaly detection as the top priority in the next one year to three years.
Machine learning (ML) applications have the potential to supercharge data science and improve analytics, enabling organizations to make data-driven decisions quickly. Successfully leveraged ML applications can boost business goals, improve customer experience (CX), and in turn grow revenue.
In a study commissioned by Capital One, Forrester Consulting surveyed 150 data management decision-makers in North America about their organizations’ ML goals, challenges, and plans to operationalize ML. Respondents revealed that ML is beginning to drive business impact, with automated anomaly detection as the top priority in the next one year to three years.
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