Without data literacy, there is no data culture. And while it’s easy to see why data literacy is important, it’s imperative to understand that one enables the other. I don't think you can create a data culture unless you prioritize three things:

  • Train people to understand why data is so important
  • Help them with the tools and data literacy skill sets that they need to make the right decisions  
  • Ensure that people understand the business and its objectives

This last priority is particularly important. Does everyone who creates data pipelines, analysis, and visualization truly understand what the business does, and how the business systems work? Can they converse with fluency about what’s tracked within the data tools and how that data can be leveraged to make certain types of decisions? 

Viewed through a business lens, data culture is broader than literacy. Literacy is just the training, the awareness, and the tactical data literacy skills. Culture is about how you ingrain tactical skills into conscious behavior. Data culture is much more than an extra work step or having the right data storage appliance. It's an intuitive, logical process that becomes part of your end-to-end thinking, regardless of what you're doing.  

I think of my own situation as Chief Data Officer. In my experience companies like to talk about how they live a true data culture, but if that culture has become so open and democratized that everyone’s an analyst, you can create a culture of data duplication and inconsistent quality instead. In data duplication cultures, there is no real source of truth. There may be plenty of data, but if it’s not aligned with any business strategies, how useful is it? You may find instead a lot of data reports that aren’t really answering a single question, and moreover, the creators aren’t using them. Is the data in your company actually producing business value? If not, then you still don’t really have the culture you need.

Data culture drives data intent

What you really want to build from your data literacy efforts is a culture of intent. In other words, you want all data to be aligned with a purpose – or in short, you want data by design. You want to make sure you have data for that purpose, but you don't want to create data for the sake of creating it. 

Storing and processing data costs money, especially if you’ve got the same data in 50 different objects. If you do, what's the source of truth? Data can’t be leveraged effectively unless there is a stated intent.

For example, let’s say your product involves telemetry. If you’re working with intent, you can more easily answer questions such as, “Do I really need to capture PII based on our intent?” If not, you can make sure that doesn't happen. 

When you create a data culture with intent and a single source of truth, efficiency shoots up. People can take the data and perform true analytics on top of it with measurably higher quality. Doing that also means you understand where the curated, governed data sets live and to use them consistently. 

Data Literacy and governance: two sides of one coin

One prevalent view I agree with is that the flip side of data literacy is good data governance. In other words, data literacy is something that good data governance drives. And when I say data governance, I tend to think about end-to-end data management, which means you have policy and data stewards and accountability over things like master data management, data quality, and data cataloging. In a healthy data culture, data governance becomes a way to drive community awareness, which in turn helps to drive literacy and culture.     

As a data leader, I recommend that you look at data culture as an intuitive thought process ingrained in end-to-end thinking, as well as an intent-driven practice to gather insights that solve problems. Culture starts with literacy, but literacy can’t take root and thrive without embedding it into achieving your organization’s goals.