Stop Siloing Data

Companies are focused on data like never before, but to really reap the benefits, it needs to be shared—and understood—throughout the organization.

Siloing data across an organization means missing opportunities—or worse, says Brett Hurt, co-founder and CEO of Austin, Texas-based

Hurt spoke with StrategicCIO360 about why transformation starts with building a data-driven culture, why silos drive tech talent away and how a data supply chain is similar to a traditional supply chain.

In your experience, what are the greatest missed opportunities for businesses when it comes to data?

In recent years, particularly since the pandemic, businesses have realized that they need to be more data-driven and started taking steps to achieve that goal through investment in data infrastructure and new tools. However, despite this movement in the right direction, data analysis and the ability to make business decisions based on data are still extremely disjointed and, in some cases, impossible because data remains largely siloed.

Siloed data has the potential to slow down everything in an organization, from decision-making to collaboration and trust between teams. Plus, it increases the chances that on-the-ground teams and executives are operating on unreliable, inaccurate or misunderstood data. This not only presents a massive risk for businesses but also causes missed opportunities for growth, product innovation, entering new markets and other success.

On top of the direct impact on businesses, failing to address the problem of siloed data also drives away tech talent. And in this hiring market, that is a significant and costly risk all on its own. The world’s top tech talent wants to work for businesses that are on the cutting edge of data innovation, not firms that continue to use data inefficiently. CIOs and other executives simply cannot afford to support a culture that frustrates incredible talent and causes them to leave, further increasing the costs of hiring new staff who may have to rebuild solutions from the bottom up.

If you combine the sunk cost of investments in data technology and staff with missed revenue opportunities because of poor decision-making, the data silo problem totals trillions of dollars.

How does a data catalog fit into the modern data stack for enterprises?

Traditional data catalogs enable companies to centralize data and create a single point of reference for understanding it. As we look to the modern data stack, it’s increasingly important to go beyond the traditional model and enable enterprises to fully engage with data, metadata and institutional knowledge from everyone at the company. This knowledge must be easily discoverable, accessible, understandable, usable and connected back to the business. It’s a new way of thinking about data management that we call agile data governance. Integrating knowledge graph technology, which is already powering major household names like Amazon, Google and Meta, is a big piece of that puzzle too.

A recent CIO survey by Deloitte found that there’s nearly an equal number of workloads running in cloud environments as compared to on-premises environments. As the world moves to a cloud-dominant environment over the next few years, data access and governance will be a top priority for most enterprises, with the goal of empowering distributed teams to own the data that they know best. A cloud-native SaaS data catalog is a foundational piece of the modern data stack that can help organizations eliminate silos, power digital transformation and deliver powerful data products.

Many executives are still unsure where to start when it comes to fully leveraging their data. What do you recommend?

In my experience, transformation must start with culture, not technology. Building a data-driven culture isn’t easy. It requires investing in new roles like data product managers, knowledge scientists and data scientists, while also making sure that those team members have been empowered and given the tools to be successful. Encouraging collaboration, contribution and data reuse are also critical elements of building a data-driven culture.

While this transformation requires both a financial and time investment, leaders should view the data supply chain similar to how they view their actual supply chain. This type of mindset shift can help conceptualize how enterprises view and collaborate around data.

How do you get entire organizations—even stakeholders who aren’t data experts—on board with a more data-driven approach?

I have found that many tech implementations are unsuccessful because they fail to consider the end user. Any data management or governance tool is only successful when it is as accessible to the “non-data people” as the “data people.” Otherwise, silos remain in place—or get even worse—and the knowledge gained through data analysis never reaches its full potential.

It can be tempting for CIOs to go for a flashy new offering with promises of transformation, but they really need to focus on technology that is intuitive, easy to use, and can gain traction and adoption throughout the company. In fact, I believe modern data catalogs can see an adoption curve similar to, if not greater than, some of the popular BI tools on the market today.

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