Today we were talking about modern analytics architecture, and I couldn't help but notice the word trust kept coming up. It should come as no surprise when I say we should only work with data that we trust, because what's the point of spending hours building a viz when we weren't even sure whether the data used is an accurate reflection of the reality. Data is the foundation of analytics, so it only makes sense that we take the steps to confirm the credibility of a data source before diving into it.
In Tableau, there is a nice certification function that helps users to find trusted data. A green tick would show up next to a data source if it has been certified as trusted data. When hovering over the tick mark, it will show you who reviewed the data source and when did they do it. Only servers, site administrators or project owners have the power to do so. You can find more information on the who and how on Tableau's website which is linked below. The green tick might also come in handy when others challenge your data source.
Other than certifying data sources, data owners can also help users to trust their data by leaving descriptions, which include information such as how was the data collected and cleaned. Being transparent with the data preparation process can significantly increase the credibility of a data source.
It might sound far-fetched but it is true that some companies would spend the beginning of meetings challenging the credibility of a data source. So it is always nice to make sure the legitimacy of a set of data before using it:)