With data increasing at a rapid pace and more companies seeing the need to compete on analytics, there is also more awareness of the essential role of data literacy. As the amount of data created everyday continues to explode, businesses are looking for every advantage they can get in order to adapt to changing situations in their markets.
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Laura Sellers, chief product officer at Collibra, believes that it is as important for organizations to place emphasis on scaling data literacy as it is to scale the amount and type of data that a business processes daily. Prior to joining the Collibra team, Sellers held product management leadership roles for more than 9 years at Alteryx, where she served as vice president of product management and product marketing through the company’s successful IPO.
Sellers recently shared her thoughts on what the last 2 years have meant for enterprises trying to keep up with the pace of data creation and the importance of democratizing data literacy so more people in the organization can use data effectively.
Collibra has always been known as a data governance company, a company that's very active in the data catalog space. Can you tell me a little bit about what you're doing now?
All of that and then more. Collibra is a platform that's about uniting organizations around data and making sure we're empowering them to be able to trust that data, to deliver accurate data to all their folks across the entire organization. The Collibra Data Intelligence Cloud consists of our underlying platform, and then on top of it sit multiple products for governance, cataloging, and privacy, as well as quality. All of those can be connected through an active metadata graph on top of that platform. The Data Intelligence Cloud is that system of engagement for data inside of any organization, similar to Salesforce for sales teams or Atlassian for the engineering teams. It is one platform to unify your whole data strategy.
How does data literacy play into that and what does data literacy mean to you?
Gartner defines data literacy as the ability to read, write, and communicate with data in context. And so Collibra’s platform is a big part of that solution. When we say “in context,” it is the ability to understand where data is coming from, as well as the analytical processes that may have taken place on the data, and then the ability for the end users to understand use cases and derive insights from the data. Our platform provides the ability to bring that visibility to the data source itself. It's a way to go in and catalog it, understand where it comes from—from both a business and technical lineage perspective—and also enable people to trust it, understand the quality of it, and protect it.
What is changing?
Data needs to be seen as a very important asset in a company. When you think of data as an asset, it really drives literacy so people truly understand: Where did the data come from? How do they protect it? And how do they use it to really drive more insights? Using money as an analogy, everybody understands money as an asset within their own life, but also within the organization. And I think the same thing goes for data—we need people to get more skilled and literate and understand where the data came from and how they can drive insights from it.
Why is this so important now?
The journey to data literacy has been going on for years. I led product from the ground up for Alteryx, which is in the self-service analytics space. I feel like data literacy was in its infancy back in the days when I was working there. It was important then, but it's even more important now because of the sheer volume of data that people have to work with and collaborate with. And I think it's been exciting seeing how data is being used more and more often with the rise of self-service analytics. In short, it's the competitive advantage. Any company that can really drive data literacy and have more people making decisions based on data is just ahead of everyone else. That culture is important, and it is something we help organizations achieve and something we're driving inside our own culture at Collibra.
What is holding back this self-sufficiency now? What are the hurdles that companies are facing?
It definitely comes back to the sheer volume of data; there's so much out there. It has been said, and I think it still holds, that 80% of a data analyst’s time is going to find and prep the data before they can actually do analysis with the data. So, if organizations don't have a way to really collect, funnel, and assess that data, it's really like they're going to be swimming up a waterfall. Having a platform or software, like what we offer at Collibra, that provides the ability to collect, assess, and curate that data so people know the data can be trusted, and that it's the right quality, is critical.
Has the COVID pandemic made things more difficult for companies, do you think?
It has driven even a more data-driven culture. There's been more migration to the cloud. Obviously, everyone in their free time during the pandemic got behind all of the streaming technology that was out there, but I think also there's been more of a push to the cloud. People are trying to find ways to embrace that more than ever before. And with the sheer amount of data, data quality has become even more important. So really making sure that data that you are pushing to the cloud and understanding the quality of it has become more and more important. But the other thing I think everyone has learned is there's more data than any humans can process all by themselves, which is where you start to see more of the AI and ML side of the world as well. With the higher volumes of data and with the fact that we do have this new hybrid working environment, data literacy just becomes more important.
What are some of the common mistakes that companies are making as they try to build data literacy into their companies and make data accessible to more users?
I think just as with any other cultural change, it does have to start from the top. By not embedding data literacy into the culture and offering kind of an actionable way for employees to learn the skills, it's impossible to achieve it. So that ongoing education is really important. And I think what we've seen is that the CDO [chief data officer] has come into the organization, but that change management and that cultural shift is where it starts to fall down. It is just so important that data literacy becomes ingrained in the culture for every employee and the way that people need to keep doing that is through continuous learning inside the organization.
Are there any specific steps, technologies, or anything else that is critical to building data literacy in an organization?
Again, it’s prioritizing the culture of education. You need to be speaking that same data language and have a data-first mindset. So, it's all about the right education and having the right leadership to drive it. Recently, I was interviewing a candidate for our head of design role, and he was speaking about how his organization was just changing its telemetry and collecting more data, but it didn’t seem like the team even knows the right questions to ask.
It comes back to the leadership to drive where the data is, assess the data, make the data available, and also help educate people on how to drive insights for competitive advantage within the organization.
What advantages does data literacy provide to organizations?
There is just so much more competitive advantage around innovation when you have that data literacy to understand where you should tweak and change things. As Peter Drucker said, "If you can't measure it, you can't improve it." The Collibra platform is software to help drive this understanding of the context of the data. Collibra is that system of engagement to be able to assess all the data inside the organization, protect that data, understand where that data came from, and also collaborate on it. What's important is that collaboration piece to understand who the stewards are within the company, who owns that dataset, and who owns the quality of that dataset and is monitoring it to make sure you're building business decisions off of trusted, high-quality data.
This interview was conducted, edited, and condensed by Joyce Wells.