With data and AI increasingly playing an essential role in organizations, leaders need practical strategies to stay ahead. Collibra Masterclass: Unified Data and AI Governance is a six-part series designed for those looking to navigate emerging trends, prepare for new regulations and accelerate their data and AI initiatives. Each session offers expert insights to help tackle today’s challenges and plan for what’s next.
In the second episode of the series, Best practices: Driving data literacy, accessibility and empowerment through data products, host Shirosh Tissera, Senior Data Intelligence Manager at Collibra, teams up with Nicola Askham – aka The Data Governance Coach – who brings over two decades of experience helping organizations get a better handle on their data. Together, they dig into what it really means to improve data literacy and accessibility, how data products can help and what it takes to build a culture where everyone feels empowered to use data with confidence. Below, we’ll cover some of the highlights from the informative session.
Why data literacy matters
Before diving into data products, it’s important to understand the foundational role of data literacy. As Nicola Askham puts it, data literacy starts with recognizing that data is part of everyone’s job – not just analysts and data scientists. It’s about understanding how to produce data accurately, use it responsibly and see its relevance in everyday tasks.
This doesn’t mean every employee needs to be an expert in analytics or building dashboards. It’s more about knowing what data is available, how to work with it appropriately and how to ask the right questions. When people across the organization have this basic level of literacy, the quality and reliability of data improve – leading to more accurate insights and better decisions.
Breaking down barriers to data access
Hand-in-hand with literacy is accessibility. Even the most data-literate workforce can’t be effective if they can’t find or access the data they need. Data often lives in silos – locked away in systems, owned by specific teams or buried in spreadsheets – which makes it difficult for others to discover and use.
This lack of access leads to inefficiencies, like duplicated work, delays in getting answers or even buying the same external data multiple times. And when people don’t know where to go or how to ask for data, they often end up with the wrong information – or none at all. Improving accessibility by having a centralized record of data assets and clear ownership helps avoid these issues and ensures teams can actually use data to make informed decisions.
Laying the foundation for AI
The prevalence of AI and GenAI has been raising the bar for both data literacy and accessibility. These technologies are powerful but only as good as the data on which they’re trained – which is why a strong foundation of data governance is more critical than ever. This ensures the quality, accuracy and integrity of the data fueling your AI efforts.
In parallel, organizations need to build AI literacy, helping business users understand what AI can and can’t do – and how it ties back to the underlying data. Without that understanding, there’s a risk of misusing AI tools or placing trust in outputs that are based on poor data. Together, strong data and AI literacy, combined with easy access to trusted data, are essential to realizing the full potential of AI across the business.
Data products: A catalyst for data empowerment
When people understand the value of data, know how to work with it and can easily get what they need, organizations are better positioned to drive real impact. That’s where data products come in. Designed to be easy to find, understand and trust, data products help make data more usable for everyone, not just data teams. Let’s take a closer look at what they are and why they’re a game changer for scaling data literacy and accessibility across the organization.
At its core, a data product is a data asset that is valuable on its own and shared with other users. Data products provide data in a way that’s packaged to be usable and valuable for a specific purpose. While seemingly similar to traditional data sets or reports, data products embody a mindset shift towards treating data as a tangible product with inherent value.
A well-designed data product typically has the following characteristics:
- Accessible: The data product must be easily obtainable by the intended users
- Understandable: The content, meaning and intended use of the data product must be clearly defined and documented
- Discoverable: Users need to know that the data product exists, where to find it and understand its potential value to their work
- Interoperable: Data products must be able to work seamlessly with other systems and tools using standardized formats and protocols to support integration and reuse
- Trustworthy: Users must have confidence in the quality and governance of the data within the product
The importance of a business-driven approach
Successful data product initiatives must be business-driven rather than solely led by technical teams. The business users are the ultimate consumers of data products, and their needs and pain points should guide the creation process. However, recognizing that business users may initially be unfamiliar with the concept of data products, Nicola recommends an “art of the possible” approach. This involves the data and analytics teams working collaboratively with the business to identify common data needs and demonstrate the potential of data products to address them.
Starting with simple, high-value data products that address widespread needs can build momentum and encourage further adoption. This iterative approach, similar to building a minimum viable product (MVP), allows for continuous feedback and ensures that the developed data products truly meet user requirements.
Designing empowering data products
To ensure data products make a meaningful impact on data literacy and accessibility, it’s important to consider these best practices for their design and implementation.
Establish foundational data governance roles
Before you begin your data product journey, it’s essential to set up core data governance roles – most notably, data owners and data stewards. Data owners provide strategic oversight and accountability, ensuring each data product aligns with business objectives. Data stewards play a critical role in maintaining trust and usability by managing data documentation, quality and adherence to governance policies.
Focus on discoverability and ease of use
Data products must be discoverable through a central data catalog or data marketplace. Additionally, their design should prioritize intuitive use, making them accessible even to non-technical users. Clear documentation outlining the purpose, content and usage of each data product is vital.
Encourage collaboration
Collaboration between technical and non-technical teams is essential. Creating an internal data marketplace or data product hub can help make this easier, acting as a space for feedback, communication and data sharing.
Build trust at every stage
For data products to be adopted, trust is key. That trust is built through strong governance, active stakeholder involvement, and continuously gathering feedback throughout the data product’s lifecycle – from design and development to discovery and adoption.
Defining success and measuring impact
Launching a data product initiative is an ongoing effort that greatly benefits from defining and measuring success. It’s not always easy, but figuring out what success looks like is key to showing the value and keeping the momentum going. Using a mix of qualitative and quantitative measures gives you a complete picture of how the initiative is actually making an impact.
- Qualitative measures might include:
- Observing a positive shift in mindset towards data-driven decision-making
- Noting increased interest data literacy across the organization
- Quantitative measures might include:
- Tracking the number of new data product requests, approvals and creations
- Monitoring the number of views and usage of available data products
- Gathering user feedback through surveys and other channels to assess the value and usability of data products
- Calculating time savings or other efficiencies gained through the use of data products
Regarding the responsibility for ensuring the ongoing success of a data product – it lies partly with the data product owners, who should monitor usage, gather feedback and ensure the product continues to meet user needs. Similarly, data consumers play a crucial role by providing feedback and actively utilizing the available data products.
Key takeaways
As organizations continue to navigate an increasingly data-driven and AI-powered world, the ability to empower users with trusted and accessible data is more important than ever. Below are a few key takeaways to guide your strategy for advancing data literacy, accessibility, and long-term data empowerment across your organization.
- Boost positive business outcomes by enhancing data literacy and accessibility: Actively work to improve understanding and access to data for all users, especially in the age of AI. This will lead to enhanced innovation and a stronger competitive edge
- Data products are the key to data empowerment: Data products bridge the gap between raw data and business needs by making data understandable and accessible to everyone, including non-technical users
- Foster trust and collaboration for sustainable success: Embedding trust in data products through governance, stakeholder involvement and user feedback, alongside promoting collaboration between technical and non-technical teams, is critical for long-term success
By putting these best practices into action and building a culture that values data literacy and accessibility, organizations can optimize the value of their data. Data products make it easier for everyone – not just data experts – to find, understand and use data with confidence. And when teams are empowered to trust the data and work together, it leads to smarter decisions, faster innovation and long-term success.
Want to learn more?
- Watch the on-demand Coliibra Masterclass webinar: Best practices: Driving data literacy, accessibility and empowerment through data products
- Read the eBook: Six best practices for building and deploying effective data products
Check out the rest of our Masterclass sessions: Collibra Masterclass series: Unified governance for data and AI.
