A skill set rarely discussed in the BI narrative is that of data literacy. Much is made of newer & more advanced visualizations, but the ability to understand what you are seeing and make smart decisions from that is incredibly valuable. Only a person with a great degree of data literacy can successfully both read & manipulate complex data to arrive at meaningful insights.


Reading & Writing

Data literacy comes in two parts: the front-end and the back-end. On the front-end a dashboard page requires the lowest degree of data literacy. Most people can read a well designed dashboard page and understand the general status of things. It is when the user advances to pages intended for critical analysis that the bar rises and users begin to drop out. Real analysis requires a data literate audience to get to the root cause of a KPI's status.


Marching hand-in-hand with front-end literacy is back-end literacy. While a great dashboard may not require much data literacy from the users it required a greater degree of data literacy from the person(s) who built it. What is the data being measured? Where does it come from? Are there compatibility issues between the data sets in an application? Building new visualizations or manipulating existing ones require familiarity with the data as well as how complex that data source is. Working with a simple data set requires relatively little data literacy but the more complex the data the greater the need for a data literate developer. Creating new objects is more than just technical development knowledge - it is understanding what you are measuring and why you want to measure it. Data literacy is often overlooked when it comes to the skill set of a great developer.


Increasing the data literacy of your organization, and yourself, is the key to spreading BI to the masses.