Sampling and information needs in the modern environment

The Data Science Revolution

Data comes from many sources: from the results of water analysis to the time, date and location of a customer complaint. The ability to turn data into information is determined by:

1. the skill of wrangling data (also making sure the data is in an appropriate electronic format that can be used in the first place!)
2. checking the data is not random and maximising its value; and
3. delivering the findings in a format that is accessible and can be clearly understood by the audience.

This, in essence, is "Data Science". Data science is used increasingly to drive the decision-making process. The value of data is growing, with digital communication it is more readily collected, but it is also becoming easier to apply data science to extract understanding, insight and knowledge. This capacity to explore data has been enhanced in the last decade with innovative assessment methods, especially ones aimed at big data, and in new ways of publishing the information that are reproducible and increase workflow. Amazingly the best tools to apply data science are available through open source (free) software.

This presentation will explore the relevance of the data science revolution to water and waste management demonstrating its challenges and opportunities, from sampling information to lab derived results, introduce some of the open source and "best" tools to apply data science; with the aim of adding value to the business.