For most executives, data democratization is a pipe dream. The idea of seeing entire teams and departments fully enabled and empowered to use data to enhance every business decision—leading to better ROI, sustained growth, and higher overall performance—feels like a far cry from the current reality.

As it stands, only 32% of the data available to enterprises is put to work, with the remaining 68% going unleveraged. In addition, 54% of executives recently reported that an inability to be nimble and compete on data presents the most significant threat that they face.

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Clearly, these statistics don’t reflect organizations that have effectively democratized data for their workforces to use to the best of their abilities. That’s a major problem, especially when we consider the rate at which business needs are changing. When a new need arises, these organizations will lack the insights and agility that would enable them to outperform competitors.

How do companies move past these obstacles to data sharing and achieve greater nimbleness and responsiveness? As executives develop a strategy for data democratization, I recommend focusing efforts on three key priorities to maximize business impact: building excellent and actionable data products, fostering greater trust in your data, and delivering no-code options that make data usable by the workforce at large.  

Build accessible data products

Data democratization hinges on all users being able to easily find data, confirm that it’s the right data for a given use, and know that it’s accurate. Consequently, I’d argue that introducing an accessible, user-friendly, high-quality data product is the most fundamental part of a well-thought-out strategy for achieving data democratization.

One of the primary obstacles to data democratization is the inability of users to find and access data. We’ve already seen that 68% of a business’s available data isn’t even used, which reveals that, while organizations may have the data users need, users can’t find it. This can happen for a variety of reasons. Perhaps there’s no search functionality that enables users to find a piece of data across disparate data tools. Or perhaps the tools they’re using lack the metadata needed to enable proper searches of the data. That lack of metadata could also make it particularly challenging for users to confirm that the data they’ve found is indeed the right data for their given application, further limiting democratization.

What an accessible data product offers is a more comprehensive set of parameters that tap into metadata to deliver greater value to users. A powerful data product empowers every user within an organization to better understand and leverage the data that’s been collected, helping to uncover deeper insights into customer behavior, market trends, and business performance. As users begin to gain more valuable insights, the success becomes contagious. In time, a greater number of users within the organization will use data products on a consistent basis, resulting in more widespread data use for better decision-making across the board.

Creating a data product capable of producing analysis-ready data, with set business definitions and metadata that make data findable and accessible, is a complex undertaking, but it’s well worth the time and effort. Armed with the right data product, organizations as a whole can make more informed decisions, improve operational efficiency, and drive growth. 

Ensure you can trust in your data

The complexity of the modern data stack presents too many opportunities for data sets to fail users, and compromise users’ trust in their data. Companies are using an ever-increasing number of disparate data tools, which in turn increases the number of transformations that data go through. A user accessing data that’s been through multiple transformations needs to know that they can trust that the data is both accurate and true to the data that was originally captured in source systems.

Clearly, this is an issue that must be addressed—especially when we consider that this lack of trust eats away at that 32% metric we saw earlier. In reality, that figure is even lower if business users don’t feel that they can trust the data available to them.

Ensuring users can trust their data requires a multi-pronged approach that should involve implementing automated data quality software, providing strong data lineage, and establishing data governance policies. As companies work toward data democratization, providing transparency, auditing abilities, and strong data governance can give users greater confidence in the data being analyzed and the insights being derived from it—leading to more widespread data use.

Building in self-service auditing functionality is another integral step that any business can take, regardless of what data tools they use. Typically, auditing has been done by more technical teams, rather than by general business users. However, this introduces an additional barrier between the average user and their data—in the form of a verification request that must first be submitted to and processed by another team.

This extra step makes it more difficult and time-consuming for users to put data to work, hindering data democratization efforts and disincentivizing users. Instead, self-service auditing is one of the most powerful ways to enhance data democratization, by ensuring that everyone has the ability to verify data as accurate and move forward with their work.

Integrate no-code data tools

Gone are the days when your only option was to hire a Ph.D. in statistics or an incredibly expensive and in-demand data scientist. Today, no-code and low-code options exist, and they can—and should—be a part of your data democratization strategy.

No-code and low-code data tools have a clear and direct impact on data democratization by immediately making it easier for everyone to interact with data. These tools not only put data use within reach of less technical people, but they also free up data professionals to focus on more valuable tasks, rather than simply being the go-between between the data and other members of the organization. No-code and low-code options enable everyone to more effectively use their time and the data at their disposal to make business decisions.

Beyond addressing the ease-of-use aspect of data democratization, no-code and low-code options also accelerate the speed at which businesses can respond to changing needs, helping to create a nimbler organization that can outperform competitors.

Put high-quality data within reach

It’s possible to take widespread data democratization from fantasy to reality, enabling all users to comfortably and successfully use data to make improved decisions. A robust data democratization strategy starts with accessible data products, ensuring trust in data, and giving users low-code or no-code options.

By focusing on these three priorities, business leaders can build an organization of confident data users, ultimately creating a more responsive business capable of delivering better customer experiences.

Vasu Sattenapalli is CEO and co-founder at RightData.

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