Despite the growing number of organizations investing in data science and machine learning (DS/ML), many still struggle to transform their investment into real business value.
According to our global survey of respondents from 22 industries, 18 countries, and 122 executives and business leaders (more than 50% in the C-suite), only 14% are currently operationalizing DS/ML. But why? What are the barriers keeping organizations from operationalizing data science and machine learning?
In this ebook, we take an in-depth look at:
- How DS/ML maturity affects digital innovation
- The lack of understanding of models currently in use
- How critical of a barrier data is to DS/ML adoption
- The amount of time needed to deploy DS/ML models
- Issues with standardized lifecycle management
And much more.