How is Data Science related to Water Utilities?
Posted on: May 24, 2023
The author - Peter Prevos - shares a little bit about his book and the challenges faced in water management.
- Can you provide an overview of the main principles of data science discussed in your book?
Data science is more than writing code and generating reports. Good data science must be useful, sound and aesthetic. For it to be useful in water management, it should positively change the reality it describes. Managers and decision-makers need actionable intelligence to deliver better water services. Data products need to be sound in the scientific sense, which means that the data and the analysis are reliable and valid. Last but certainly, not least, the way the result of our analysis is presented should be aesthetic. Not in the sense of being beautiful, but easy to understand with a simple and consistent design or text and graphics to ensure that the consumer of the results draws the correct conclusion.
- How does this book address the specific needs and challenges faced by water professionals in managing water utilities today?
This book is a basic introduction to using code to solve typic problems water professionals face. I have chosen case studies from my years of experience as a water engineer, such as analysing water quality and consumption patterns. But water utilities also need to understand the customer experience, so one case study deals with analysing survey data. Most books about data science use abstract examples of stock data sets, such as flowers or 1970s cars. This book is written from the perspective of a practitioner.
- What inspired you to write about this topic and why now?
I started teaching data science to fellow water professionals in Australia in 2018 through Water Research Australia. This course has been well attended ever since, with most sessions sold out. As I developed the course notes, the book emerged from my experience as the best way to teach this abstract topic to people with practical needs.
- In your opinion, what is the biggest challenge in urban water management?
The biggest challenge in urban water management is climate change's impact and our systems' resilience. The increasing temperatures reduce the amount of available fresh water for agricultural, industrial, and agricultural use and reduce the water quality in our rivers and aquafers. As a result, water utilities are embracing new digital technologies to monitor their systems to better manage their scarce resources. Data science plays a vital role in making sense of the data that these digital systems collect.
- Lastly, what are the take aways from "Data Science for Water Utilities: Data as Source of Value" for water professionals and/or readers?
To fully embrace the benefits of digitisation in water utilities, water professionals need to enhance their capabilities in data analysis. The main takeaway from this book is that using spreadsheets is no longer sustainable and that learning how to write code to analyse data is an essential skill. The second aspect that readers can take from the book is the systematic approach to solving data problems and following principles to create actionable intelligence that will help us o secure plentiful and safe water into the future.