Data Governance - Structure

Peter Johnson , CEO, WaterOutlook

Here's the next instalment of Data Governance 101. Once you have defined why you need the data, the next part of a data governance structure is to define the data sinks and sources:

·???????? Where is it coming from?

·???????? Where does it reside?

·???????? Where is it consumed?

This is the technical part of data collection.? There are several aspects to data collection: connectivity, cyber security, archiving, data access, time zone management, data latency, legislative data requirements, data ownership, and privacy requirements etc. The collection and long-term storage of data is best left to the specialists and not something that should be tackled by those without up-to-date in-depth knowledge and skills in data collection who also understands the legislative requirements associated with that data.

When data is collected/accessed, then effective analysis can be run.? This should change the data to information. This information should then be used to drive the desired behaviours.? As a simple municipal water supply example, if data from a water reservoir shows it is 40% full, what does that mean? In winter it may mean that there is two days’ storage but in summer it may only mean six hours storage. The data is the same but the information, and therefore the behaviours that ensue from it, are different.

Then there’s the issue of data density. It’s easy to be seduced by mega-data lakes of high-density data to 16 significant figures.? In other words, large repositories of data that have been collected because it can be.? Is this the right strategy for your data? Stay tuned and we’ll examine this next time – drop us a line for a chat.