How to build a strong data democratization strategy (and why you need one)

Brainstorming ideas for a new product feature is exciting. But that enthusiasm can quickly fizzle out when you try to back up your proposal with data that’s scattered across departments or hard to access. Plus, sometimes you need to wait days for an analyst to generate a report. It can be frustrating and slows you down. 

That’s where data democratization comes into play. It breaks down barriers and makes data accessible to you and everyone on your team. No more waiting, no more silos—just quick, easy access to the insights that help you make smart, innovative decisions. 

This article will explore what it takes to build a true data democracy—what data democratization means, why it's important, and how you can achieve it.

What is data democratization? 

Data democratization is the process of making data accessible to everyone, regardless of their technical abilities. The goal is to ensure every member of your organization—even non-specialists—easily get the data they need, when they need it, without asking for help. 

Why do you need data democratization? 

At its core, data democratization is all about solving the data challenges people face every day. Most of them relate to data architecture—the blueprint for how your company’s data is organized and used. This structural design organizes data flows and storage solutions, ensuring the right data is available to the right people at the right time.

By simplifying all the steps involved in handling information, a data democracy

• Optimizes data storage architecture so data is easier to find and use

• Removes barriers so teams can share and use information more freely

• Streamlines data management to make data processing simpler and more intuitive 

• Improves data security to reduce the chances of data breaches and leaks

This puts valuable data into the hands of those who can use it best. When teams work with the right data, it empowers them to make informed decisions that benefit everyone—both individuals and your business as a whole. It doesn’t just help them solve problems, but also prompts them to be curious, innovative, and ask “How else can I use this data?”

Data democratization vs. data governance

Data democratization and data governance are related concepts but they aren’t the same.

• Data democratization is about making data usable and accessible to a wider audience

• Data governance uses policies to ensure this data is managed properly and maintains its quality and security 

Both are essential to create a truly data-driven business and product. Together, they help keep your data accurate, reliable, and protected, while providing every employee with the support and resources they need to reap the full benefits.

How to build a data democratization strategy 

Democratizing data sounds good on paper, but making it a reality can be challenging. A data democratization strategy lays out a clear plan with steps, guidance, and the right tools to make it happen.

Let’s look at how you and your organization can deliver on data democratization initiatives.

1. Evaluate your current data landscape

Look at what data you have, who’s using it, and how it’s currently being accessed and managed. Understanding the current status of how your data is managed helps you see what changes you need to make.

Think about how different teams typically work with data and the tools and resources they use to accomplish their jobs to be done (JTBDs). For example,

• Product relies on user feedback and product analytics tools to identify trends, build features, and drive customer value

• Marketing uses analytics platforms to track campaign performance and customer behavior data to create more engaging content

• Growth leverages data to run experiments like A/B tests on optimization platforms and generate personalized digital experiences

• Sales works with CRM systems to analyze customer interactions, identify prospects more likely to convert, and refine sales tactics 

• Executives use business intelligence tools to monitor performance and make informed decisions about future investments

Don’t just assume you know how people across your company work with data—ask them about it. Questions like “How do you rely on data to achieve your goals, and what’s stopping you from reaching them?” and “What would you like to do with data that you haven’t analyzed yet?” help keep your data objectives inclusive and realistic.

Then, examine what’s working and what isn’t. Look for any bottlenecks and spots where better tools or more access might help your teammates achieve their goals faster. The objective here is to understand the quality of your data and how it flows (or doesn’t) between areas of the organization. 

2. Map out your data democratization framework

This framework will not only guide implementation, but also ensure your data democratization strategy aligns with business objectives and employee needs and expectations. This keeps everyone that works with data productive and in line with what you’re trying to achieve: a smooth, data-driven experience. 

Figure out what you want to achieve with data democratization and create a plan based on those goals:

• Define your data objectives: you might want to increase revenue, improve profits, or make it easier to manage and move your data as it grows and your company scales

• Create policies for data accessibility: use your new understanding of data operations to find opportunities to change, create, and implement policies that take data out of silos and put it into the hands of users. This is also a good time to define how tools, automation, and AI can help make this vision a reality, which brings us to our next step.

3. Choose the right data democratization tools

Data democratization starts with the right data architecture, but is amplified by the right toolkit. 

Invest in products that help your team work with data efficiently to derive insights and make data-led decisions without relying on others. Depending on its size and data maturity, your company could benefit from

• Data visualization tools: turn complex data into easy-to-understand charts and graphs. Instead of wading through raw numbers, marketing teams that need to know how a campaign is performing use tools like Tableau or Power BI to create visual reports that make trends and insights pop. 

• Open data platforms: centralize publicly available data, allowing anyone to access and use the data for their own purposes. For instance, product teams use Data.gov or the World Bank's Open Data Portal to find publicly available datasets for market research, competitive analysis, user demographics and preferences, and geographic and economic data. 

• Data catalogs: provide a searchable index of available data sets, making it easier for users to find and access the data they need. Data catalog tools like CKAN or Socrata help digital teams find specific data sets quickly, without needing to hunt for them through countless repositories.

• Data governance tools: help manage and protect your data assets, ensuring that data is accurate, secure, and compliant with relevant regulations. Marketing teams that handle customer data and need to keep it secure and compliant use tools like Collibra or Informatica that help manage and enforce the right rules and checks. 

• Self-service analytics tools: enable users to perform data analysis tasks on their own without relying on your devs departments or data science teams. Self-service analytics tools like Contentsquare or Google Analytics empower your teams to not only access data but also to make data reporting and analysis a part of their daily routine. 

How to use Contentsquare for data democratization

Contentsquare’s experience intelligence platform brings clarity to how you collect and use customer data. 

In a data democracy, product, marketing, and analytics teams use these Contentsquare capabilities and features to make informed decisions and optimize user experiences, without needing to ask or wait for specialized help:

• AI insights: understand key metrics and get AI-powered summaries in real time, paired with smart alerts and recommendations from Contentsquare’s AI, Sense. Teams can understand their customers’ digital experiences and make data-driven decisions by simply asking simple questions of Sense via a user-friendly interface. And, with a centralized view of user behavior data, like where, how, and why they interact the way they do with your product or website, it’s easy for everyone to understand and use customer insights.

• Data integration: combine user experience data with insights from other tools, such as CRM or A/B testing platforms. These integrations help unify data from various sources for a comprehensive view of user behavior and better decision-making across departments. 

• Session Replay: watch replays of how real users interact with products, websites, or apps. Reviewing session replays helps your team understand how your customers use different features, where they might get stuck, and what you could improve to enhance customer experience. 

• Heatmaps: see where users are clicking, scrolling, and spending time on a page. Heatmaps provide visual insights into user engagement with different page elements, like call-to-actions (CTAs) and images, helping teams optimize design and functionality based on actual user interactions.

• Journey Analysis: map out your entire user journey, from initial visit to final conversion. This feature allows teams to see where users encounter obstacles or drop off, providing valuable insights to improve the overall user experience at every step.

With a simple set-up and powerful insights, everyone can easily get to work and focus on their tasks without dealing with complex data processes. 

Contentsquare provides your teams with user-friendly tools they need to analyze and interpret data effectively

4. Develop a data literacy training program

For a novice end-user, data analytics can be overwhelming. To truly democratize data and make it accessible to as many people as possible, those individuals need the necessary skills and knowledge to understand and effectively use that data. 

This means investing in training programs to improve data literacy and ensuring that data is presented in a way that’s clear and easy to understand.

• Educate employees on how data democratization improves their job performance and creates better outcomes

• Make sure everyone understands the scope, significance, and processes surrounding the data

• Cover each data platform’s capabilities, how to navigate it, and step-by-step approaches to entering, accessing, and interpreting data

• Look to data experts and leaders who have an existing understanding and expertise in this area to help get everyone on board and make data literacy part of the new hire onboarding process

5. Establish data governance policies

For data democratization to be effective, users need to trust the data they’re accessing. If they doubt its accuracy or relevance, they won’t use it. This is where data governance policies come into play, ensuring data is reliable and up to standard. 

Strong data governance policies also keep data secure and private. These guidelines define how data should be protected, who can access it, and under what circumstances.

Here’s how to set up some rules to ensure data quality, security, and compliance while maintaining open access: 

• Build confidence in data quality: data programs are useless if users don’t have confidence in the quality of accessible information. Using a solution like Master Data Management (MDM)—which creates a single master data record for each person or place in a business—is a good way to maintain and solve quality-related issues. By building a trusted and authoritative view of your company’s data, you better manage and share it across the business with confidence.

• Establish policies for data security and privacy: data accessibility doesn’t mean universal access for everyone, everywhere. Keep your data safe and efficient by making sure teams can only access data that suits their understanding, skills, and needs. This gives employees the resources and support they need to feel confident and capable in their data, as well as their ability to use it safely and responsibly.

• Define roles and responsibilities for data management: clear roles and responsibilities make it easier to democratize data. When everyone knows their part in the data ecosystem, it becomes easier to provide broad access to data without compromising on quality or security. Key roles to consider are data stewards (who manage and oversee data sets), data custodians (who handle data storage, security, and backup), and data users (who access and use the data for their daily tasks).  

• Outline procedures for data sharing and collaboration: these procedures make sure that you responsibly and effectively share your data across your company or with external partners. For example, this would be a great time to set up a confidentiality agreement for sharing sales data with a third-party service provider, or declare that customer data should only be used for analysis to improve user experience, and not for any unauthorized marketing activities. 

By setting clear expectations and guidelines, you open up data so that anyone in the organization can benefit from it, without exposing yourself to legal or security risks.

Next steps to data democratization

It’s now time to roll out your data democratization strategy, track its performance, and adjust as necessary. Because you’ve put in the effort, you’ll see the results: a clear and intuitive approach that makes it easier for everyone to actually want to work with data. 

As everyone begins to understand their role in the process, your organization will get behind your data democratization strategy, supporting you in improving existing processes and tools and adding new ones. Together, you’re improving efficiency, uncovering new insights, and creating a culture where people are excited about making the most of data. 

FAQs about data democratization