Decoding Data Culture: Highlights from the State of Data Culture Maturity Webinar

By Anthony Zumpano

Published on December 15, 2023

Illustration for Alation's Decoding Data Culture Highlights from the State of Data Culture Maturity Webinar blog post

Although I work for a data intelligence company, it’s not unusual for me to declare that solutions and tools alone cannot solve business challenges. 

Achieving success with data initiatives relies on both the organization’s people and its mindset. These factors together contribute to the formation of a data culture, an environment where data is trusted, used, and embedded in decision-making processes.

Our recent State of Data Culture Maturity Research Report, based on a survey of nearly 300 global data professionals, examined the critical four pillars of data culture maturity: data leadership, data search & discovery, data literacy, and data governance. It revealed how well organizations around the globe are fostering a data culture and their roadblocks to achieving one.

Our related webinar broke down the results of the report, with the speakers — Julie Smith, Alation’s Director of Data & Analytics; Billy Tilson, Enterprise Data Architect at GoDaddy; and Dr. Jonathan Reichental, a professor and consultant and author of Data Governance for Dummies — offering additional insights around data culture and its pillars.

You’re invited to watch the replay, but here are some highlights.

Defining “data culture”

According to Reichental, finding a widely accepted definition of “data culture” can be elusive. “We sort of understand these words, but when we're asked what they actually mean, that's when it becomes a little bit more difficult.” He noted that a company’s culture is defined by behavior; when applied to data, culture is “how we overtly demonstrate the value of data in our organization.”

Tillson acknowledged that as an engineer, “the technology side is actually not that hard. The people side is much, much harder.” At GoDaddy, he surveys the company’s data users to gauge their feelings on their data — for example,  whether it’s trusted and easy to find — which is a better metric for data culture than mere data usage. He contrasted a culture of mistrust (where data is constantly questioned) with a “data first” culture (where data is embedded in everything from decisions to product launches). He said, “When you win arguments with data,” because that data is trusted, “you know you have a very rich data culture.”

The role of data leadership 

The main difference between last year’s report and our recent one was the inclusion of data leadership in the data culture discussion. Data leadership is a fundamental pillar in fostering a robust data culture within organizations. As Reichental emphasized, data culture is defined by behavior, "how we overtly demonstrate the value of data in our organization." Therefore, it’s not surprising that effective leadership plays a pivotal role in setting the tone and behavior surrounding data within an organization.

Tilson mentioned the importance of growing data initiatives from the ground up, with people talking about data at the grassroots level. At the same time, he tied the success of this kind of data ownership — ”data is not just someone's responsibility over here or there; it's actually everyone's responsibility” — to data leadership.

“This is where strong leadership really helps in making people accountable for their data,” he said. “Bad data doesn't start with one person. There's a supply chain of data, and you really need to get it right at the beginning because it's very hard to fix it down the line — and then no one benefits from it.” It takes data leadership to get everyone involved and ensure accountability for producing good data (and fixing bad data).

Strong data leadership empowers organizations to use data better. Focusing on the value of data, and making data part of decision-making, results in more successful data projects. In fact, the survey found that organizations with strong leaders were two times more likely to do better than their money goals.

Catalog, curate, establish conventions 

Being a data-first organization doesn’t mean dumping data somewhere and organizing it later. “Having a comprehensive [data] catalog is key to making sure you have everything in a single central place because data goes everywhere,” Tilson said. “I don't care how strict your architecture is, you're going to get data coming into various places. It’s not all going to be centralized.”

Once your data is cataloged, you should curate it. This is not just about adding metadata, but also prioritizing the most valuable data. “Not all data is created equal,” he said, noting that GoDaddy has a data tiering process “so we don’t try to boil the ocean.”

Finally, Tilson stressed the importance of establishing terms and naming conventions. “Everything in the [data] lake gets reviewed by my governance team in terms of naming conventions and making sure we're using the right terms.” 

The critical role of data discovery… 

One of the troubling survey results was that only 18% of respondents were “very confident” that they could trust the data they discover. “If you can't find the data you want and be confident in it, does anything else matter?” Reichental asked. “At that point, you can't make decisions. You can't drive the business outcomes you want.”

The speakers discussed the need for implementing tools and practices that enable users to find relevant datasets efficiently, as well as the top data discovery challenges. These include inadequate metadata, a lack of standardized naming conventions, and the sheer volume of data that makes it difficult for users to locate what they need.

…balanced with data security

At the same time, greater access to greater amounts of data increases risk, Reichental noted. He stressed the importance of assigning data owners to important datasets. “There are going to be core datasets that are important to you — maybe your customer list or your current price list. For each of those, do you have somebody who comes into work every day and worries about them? Do they worry whether that dataset is current or high quality?” If not, he said, that data is simply adrift with elevated risk.

“If you want to balance accessibility and quality with the elevated risks that come with that,” Reichental concluded, “assign responsible data owners.”

At GoDaddy, Tilson has observed data governance awareness becoming an integral and natural part of the organization's workflow. The foundation for that is an increase in trust in data. At one time, less than half of GoDaddy’s data users said they trust their data, but now more than 80% do.  Increased data trust has coincided with an increase in data governance awareness — “It’s no longer a dirty word,” Tilson said. “People who would sort of roll their eyes when it came to governance now see the value of it. It transforms data from something you struggle with to something that's easy to consume and use.” 

Planting the seeds to cultivate culture

The webinar speakers highlighted a crucial reality in the realm of data initiatives: Success is not solely dependent on sophisticated platforms and tools. Instead, it hinges on fostering a robust data culture within an organization. The four pillars — data leadership, search and discovery, literacy, and governance — stand out as critical elements in this cultural transformation.

The human factor and organizational mindset are central to overcoming challenges and driving meaningful outcomes in the complex data landscape. The journey toward a data-first culture involves cataloging, curating, and establishing conventions, coupled with a balanced approach to data discovery and security. And, of course, data leadership offers the top-down empowerment to fuel a bottom-up data culture:

  • The top-down approach helps establish a framework, allocate resources, and sets expectations for managing and leveraging data.

  • Simultaneously, a bottom-up data culture involves active participation and engagement from employees at various levels to value data, contribute to its quality, and employ it in their day-to-day work.

The overarching message is clear — cultivating a data culture is not just a strategic choice; it is the key to unleashing the true potential of data in today's dynamic business environment.

Want a deeper dive? Watch the replay of The State of Data Culture Maturity Today: Research Insights.

  • Defining “data culture”
  • The role of data leadership 
  • Catalog, curate, establish conventions 
  • The critical role of data discovery… 
  • …balanced with data security
  • Planting the seeds to cultivate culture
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