This book is based on 25 years of learning and experience working in data analytics.
Many things have changed during that time, but I am forever indebted to the great
managers I served under for their leadership, inspiration, and coaching. I hope to grow
others in the same way
Unfortunately, the lack of maturity means there is plenty of evidence that despite heavy
investment in data science returns have not been uniformly positive and the majority of
organizations fail to create business value from their investments in data. According to
Forrester Research, only 22% of companies are currently seeing a significant return from
data science expenditures.1 Most data science implementations are either laptop-based
research projects that never impact customers, local applications that are not built to
scale for production workflows, or high-cost IT projects.
Despite high failure rates, prescriptions and discussions remain the same. Many data
scientists talk about how to create machine learning or AI models, but not many speak
about getting them into production, a live reliable operational environment that serves
customers. Algorithms are just the tip of the iceberg when it comes to creating business
and customer value from data.