In today’s rapidly evolving business landscape, data is no longer just a byproduct of operations; it’s the fuel that drives strategic decisions, innovation and competitive advantage. Organizations that can harness the power of their data effectively are the ones that will thrive. In our recent webinar, Data products 101: empowering faster, more confident decision-making, we teamed up with SAP to explore how data products are revolutionizing the way organizations approach the management and utilization of data.
Here, we’ll summarize key takeaways from the webinar, including what data products are, why they’re crucial and how to implement them effectively in your organization – featuring a compelling real-world success story from SAP.
So, what are data products?
Before exploring the benefits and implementation of data products, it’s crucial to understand what they are and why they matter. Peter Princen, Sr. Director of Product Management at Collibra, describes a data product as a reusable artifact that bundles data with all the essential elements needed to understand, access and use it. Think of it as a pre-packaged data solution designed to address specific business needs. Instead of raw, scattered data, a data product offers a curated and easily digestible resource.
This definition highlights the key attributes that make data products so valuable:
- Data: This is the core of the data product — the actual information itself. This could be in the form of a table, view, report or even an AI/ML model. The key here is that the data component should be accurate and well-organized to facilitate meaningful insights
- Context: This includes all the auxiliary information needed to understand and effectively use the data asset. This might include its business use case, domain details, ownership information, semantic context, data quality metrics and privacy considerations. Without this crucial context, data lacks the necessary meaning to drive informed decisions
- Access: This component defines how users can retrieve and interact with the data asset. This may include various methods, such as SQL interfaces, APIs or other access points that ensure a seamless user experience. Access also includes enforced policies to ensure compliance and security
In our video, “What is a data product?,” Peter provides a great analogy, comparing a data product to an electrical appliance purchased at a store:
When you buy an electrical appliance, you don’t just receive the device itself – it comes neatly packaged with essential information to help you understand its value and use it effectively. The box highlights the appliance’s key features and benefits. Inside, you’ll find a manual with detailed instructions, warranty terms, safety guidelines and certifications (e.g., CE or UL). You’ll also get important performance details, such as power consumption and operational limits.
Data products follow a similar approach. When you access them through a data marketplace, you don’t just get raw data – you receive a comprehensive package. You’ll gain insights into the business case the data product supports, guidelines on permissible usage through active data sharing agreements and clear expectations around performance, including latency, uptime and data quality through the data contract. Access instructions and interface details are also clearly outlined, making it easier for you to realize the full value of the data.
The main takeaway of the appliance analogy is that like a consumer product, a data product is a ready-to-use, well-documented package that provides all the necessary information for its user, including context, access and the data itself. This helps to make data more accessible and understandable for a wider range of users.
What are the benefits of data products?
Data products are essential for organizations aiming to harness the full potential of their data. They’re a fundamental shift in how data is managed and consumed. Now that we’ve established what data products are, let’s explore the transformative benefits they bring to organizations:
- Alignment with business goals and AI readiness: Data products help ensure that data management efforts directly support overarching business objectives and AI initiatives. They provide high-quality, compliant and relevant data that is specifically assembled for a particular use case, improving decision-making and the performance of AI models
- Empowered self-service access, data democratization and innovation: By providing accessible, high-quality data to various teams, data products break down departmental silos and foster a data-driven culture. They empower stakeholders to access the information they need without relying on specialists or IT bottlenecks. As noted in an survey by IDC, 44% of respondents reported they don’t have access to the data they need to do their jobs – this is a problem that data products help solve. Additionally, accessible, high-quality data enables teams to more efficiently develop new analytics, applications or services and respond quickly to market shifts. And the ability to easily discover and use data fuels creativity, driving innovation
- Improved productivity and reduced costs: One-third of executives rank timely data delivery as critical to improving operations. Data products deliver accurate and timely information, enabling stakeholders to make informed decisions more efficiently. Additionally, by offering reusable data assets, data products eliminate the need to repeatedly recreate the same datasets (or other data assets) for different use cases, thus saving significant time and resources
- Enhanced accountability and compliance: Data products incorporate structured frameworks and clear ownership models that ensure responsible data management and reduce the risk of non-compliance with data governance policies and regulations
Best practices for building and deploying data products
Understanding the benefits is just the beginning. To truly maximize the value of data products, organizations need to follow proven best practices for designing and deploying them. These are some the key best practices covered during the session:
1. Have a clearly defined purpose and value
Start with a clear understanding of what problem or business question the data product is designed to address. Frame each goal in terms of the potential benefits to your organization, such as competitive advantage, improved decision-making and cost reduction.
2. Focus on usability
Design data products with the end-user in mind, ensuring they are intuitive and meet their needs. Consider user roles such as executives, marketing teams and financial analysts. Ask, “who is our target audience, and how will they use this data product?”
3. Optimize discoverability and accessibility
Host data products in a well-organized repository like a data marketplace, and make them easily searchable by incorporating relevant metadata and tags. Ensure the user interface is intuitive, with clear descriptions and labeled methods for accessing the data.
4. Ensure reliability and trustworthiness
Provide comprehensive documentation that details the source of the data and its lineage, for example. Display data quality metrics, certify trustworthy data products and enable crowdsourced feedback through ratings and reviews.
5. Consider integration and interoperability standards
Use well-known data standards such as JSON, form a governance committee, appoint data stewards and leverage APIs, for example, to ensure that data products meet organizational standards for interoperability.
6. Consider scalability and maintainability
Establish a robust data governance framework to maintain compliance and consistency as data products scale. Define lifecycle stages for data products. Engage users early, use an iterative development approach and continuously collect feedback.
Critical capabilities for data product management
To successfully build and scale data products, organizations must equip themselves with the right tools and capabilities. Let’s break down a few of most critical elements for effective management:
- Flexible data product framework: Organizations need pre-built, out-of-the-box solutions that are also extendable or customizable to fit specific needs. These should allow for the easy definition of data product components, such as business use cases, data contracts and lifecycle stages
- Seamless access and collaboration: A robust data marketplace is essential as a central hub where users can easily find and access data products. Features such as advanced search, filters, collaboration tools and detailed asset views enhance the user experience
- Automated data access management: Implement protocols that ensure the right people have access to the right data, while complying with data privacy and protection standards. Flexible options for access request fulfillment, whether automated through workflows or integrated with tools like Jira, ensures timely access and delivery
- Usage tracking and reporting: Use analytics and monitoring tools to track data product usage, understand which data products are most valuable and identify user behavior trends to guide future development and prioritization efforts
SAP’s data products success story: A real-world example
Theory is one thing, but how does it translate into real-world success? SAP’s journey offers an example of how data products can deliver tangible results and democratize access to data. The global technology leader has embraced a data product approach with Collibra. As guest speakers, Oliver Huth, Head of Platform – SAP Enterprise Analytics, and Bastian Finkel, Team Lead – Democratize Governance, described: SAP’s vision is to achieve AI-powered, data-driven decision-making for every employee. Their journey has involved a transition from manual reporting in silos to a model that offers centrally delivered data products, governance and automation.
SAP leverages Collibra as the primary platform for data product consumers and as a central hub for workflows and governance. SAP Datasphere is used for modeling, consuming and provisioning data products. This integration allows for real-time synchronization of metadata and processes, ensuring data consistency and accuracy. At the time of the webinar, SAP had 598 data products (in all statuses) within their Data for All Hub, with 270 published. This demonstrates the scale of their deployment and the value they’re deriving from their data products initiative.
The future of data: Data products and democratization
As SAP’s story demonstrates, data products are more than just a trend; they represent a fundamental shift in how organizations manage and leverage data. By adopting a data-as-a-product mindset and implementing effective data products, companies can unlock new opportunities for innovation, enhance decision-making and achieve significant business advantages. The goal is to foster a data-driven culture where data is readily available, understandable and trusted.
Next steps
Ready to dive deeper into the world of data products? Here’s how you can learn more and start transforming your organization’s approach to data management.
To learn more:
- Watch the on-demand webinar: Data products 101: empowering faster, more confident decision-making
- Read our ebook: Six best practices for building and deploying effective data products
- Check out this session recording: Data Citizens Circles: Deploying data products at scale
