Today, the vast majority of organizations realize they need to digitally transform to compete. Many organizations want to accelerate this change, and data science tools such as machine learning are at the heart of this.
Machine learning—the ability of systems to learn from data with minimal human intervention—has been around for decades. Over the past five years, however, organizations have begun to embrace the technology in earnest.
For instance, machine learning is used in marketing to better understand customer behavior and predict churn. It is being used in operations to predict when a part might fail. It is even used in HR for employee retention. Why? Because the value of machine learning is real—TDWI research indicates that those organizations that utilize more advanced techniques such as machine learning are more likely to measure a top- or bottom-line impact than those that do not.
This checklist report focuses on six technology considerations for successful machine learning and data science. We will see that a cloud data platform can help with many of the items presented in this report.
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