Pervasive data science is becoming a core enabler of business innovation and competition. Given this importance, it’s worth examining the context of data science to consider its trajectory and future value.
In my view, primary challenges around data science for business leaders comes from three sources:
1. Business people do not always understand the power and implications of what’s possible with data science and machine learning. The impact on business models, operations, and customers can be profound.
2. Lack of available data to feed the machine learning beast. Without historical or other data, machine learning has little value. Aggregating useful data can be expensive and time-consuming.
3. Insufficient talent and resources to create models and set up analyses that can best serve users and customers. Making effective use of data science demands a different kind of thought than traditional analytics; even a culture shift, so it’s hard for established organizations to adapt quickly.
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