Chapter 2
Considering the Inherent Complexity in Data Science
IN THIS CHAPTER
Understanding why data science is inherently complex
Realizing the potential in complexity
Avoiding common pitfalls
Managing complexity
Cities are complex systems, and city policies are typically made in complex environments where many factors covering a whole spectrum of social, environmental, economic, and technological factors must be taken into consideration. However, in recent years, urban complexities have been better managed by evolutions in data science. The ability to perform urban modeling and simulate different future scenarios based on actual data has opened up many new possibilities related to urban planning and investments. These evolutions in data science have enabled government agencies to better understand complex urban issues, anticipate possible scenarios, and make the best policy and investment decisions.
But what does complexity really mean and refer to? Well, in my view, society has the general misconception that complexity is always bad. Yes, the simplest solution is often the best ...
Get Data Science Strategy For Dummies now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.