In most categories, maturity is a quality that comes effortlessly to the aged and arduously to the young--not so for data maturity. When it comes to data, today's startups spring to life already pushing the boundaries of its collection, harnessing its insights, and leaning on AI to make sense of its root causes. Despite their bound booklets titled "Digitization Strategy" and secured rooms labeled "Lab of the Future," titans of industry are challenged with wriggling their way out of longstanding practices, breaking free of tired infrastructure, and asserting their way to modern data practices over the objections of sometimes thousands of internal stakeholders.

Digitization is essential for delivering these centralized water collection services and supporting efficient urbanization. It allows networks to benefit from online connectivity and management platforms that feed on information (Big Data) and can handle data far more effectively than can human operators. Commonly known as Artificial Intelligence (AI) systems, these revolutionary processes have advanced the way wastewater networks can be managed, helping to protect Wastewater Treatment Plants from damage, maximizing process efficiencies and enabling expanded water reuse projects. Digitizing a city's wastewater networks through AI starts with good data. To understand how such a system is able to provide operational wastewater intelligence, it is important to understand Big Data, AI, Machine Learning and their applications.