In the rapidly evolving landscape of data management, the concept of data products has emerged as a cornerstone for effective data utilization and governance. Industry experts have shed light on the critical nature of data products, their distinction from data assets, and their pivotal role in data marketplaces. As organizations strive to maximize the value of their data, understanding and managing data products becomes increasingly essential. To help achieve this, the EDM Council has formed the Data Products and Data Marketplaces Special Interest Group in which industry participants are actively addressing these concepts and opportunities with the goal of defining best practices.
What Is a Data Product?
A data product is defined as a rational and governed collection of data and associated artifacts managed together to meet specific criteria. This definition underscores the importance of a clear and consistent management approach, ensuring that data products are comprehensive solutions designed to address specific business needs. Establishing a specific use case and understanding the value of the data product are crucial for developing data products that align with organizational goals because without a clear purpose and measurable value, data products risk becoming just another set of data assets without delivering significant benefits.
While all data products are data assets, not all data assets qualify as data products. In the public domain, there are references to “data assets,” “data as assets,” and “data as products.” However, our Data Products and Data Marketplaces working group chose to lay out the criteria for bona fide data products. The differentiation between assets and products is a useful categorical distinction, but it is not what makes data products clearly defined. What makes data products clearly defined are the specific criteria our working group established for what would constitute a data product, including the criterion that it must be identifiable as a data product to would-be consumers in order to be a bona fide data product. By establishing a concrete definition, organizations can streamline their data management practices and ensure that their data products deliver tangible value.
The Role of Data Products in Data Marketplaces
Data products play a crucial role in data marketplaces, platforms where data products can be discovered, accessed, and utilized by various stakeholders. It is essential to have well-defined data products when considering a data marketplace. Without clearly defined and managed data products, the effectiveness of a data marketplace is significantly diminished.
Data marketplaces provide a structured environment where data products can be cataloged, accessed, and utilized by different departments or external partners. This setup ensures that data products are not only available, but also discoverable and understandable. For a data marketplace to function optimally, the data products it hosts must be well-documented and adhere to a certain level of quality and governance. This necessity underscores the importance of having robust data product management practices in place.
Return on Investment (ROI) of Data Products
So, where do we see the advantages of a clearly defined data product? One of the key benefits of data products is their potential to enhance the ROI of data. By providing a structured and governed approach to managing data, data products help organizations derive more value from their data. This is achieved through several mechanisms:
- Enabling data-driven decisions — Data products provide reliable and consistent data that organizations can use to make informed decisions. This reliability increases trust in the data, leading to better decision-making and improved business outcomes.
- Ensuring regulatory and corporate compliance — Data products help organizations meet regulatory requirements by providing clear documentation of data lineage, quality, and governance. This compliance not only avoids potential legal issues, but also builds trust with customers and stakeholders. Regulatory compliance is a significant concern for many organizations, and data products can play a crucial role in ensuring that data practices align with legal and regulatory standards. By having well-governed data products, organizations can demonstrate their commitment to compliance, thereby enhancing their reputation and reducing the risk of regulatory penalties.
- Understanding data value — By quantifying the value of data through data products, organizations can better understand the monetary and non-monetary benefits of their data. This understanding allows for more strategic investments in data management and analytics. Data products facilitate better data management throughout their lifecycle, ensuring that data remains useful and relevant, thereby maximizing its value. By providing a clear framework for evaluating data, data products help organizations make informed decisions about where to allocate resources and how to optimize their data assets.
Implementing Data Products: The Product Lifecycle (NIST)
Managing data products involves a lifecycle approach with several stages: ideation, design, build, deploy, monitor and maintain, and retire.
- Ideation involves identifying the business need or problem that the data product will address. This stage is critical as it sets the foundation for the entire data product lifecycle.
- Design involves collaborating with IT and business stakeholders to define the data requirements and design the data product. This collaboration is essential for ensuring that the data product meets the needs of all stakeholders and aligns with organizational goals while defining the governance framework for the data product.
- Build involves developing the data product based on the defined requirements. This stage includes data collection, cleaning, and integration, and the development of any necessary algorithms or analytics.
- Deploy involves making the data product available for consumption through a data marketplace or other delivery mechanisms. The deployment phase is critical for ensuring that the data product is accessible to those who need it and can deliver value to the organization.
- Monitor and Maintain involves continuously assessing the data product’s usage and effectiveness, making necessary adjustments to ensure it remains valuable. This stage includes regular updates and improvements to the data product, and ongoing governance to ensure data quality and compliance.
- Retire involves decommissioning the data product when it is no longer useful or relevant. This stage includes archiving the data product, ensuring that any associated data is securely stored or disposed of, and resources are allocated to the most valuable products.
This lifecycle approach ensures that data products are consistently managed and maintained, providing ongoing value to the organization. By following a structured lifecycle approach, organizations can ensure that their data products are developed, deployed, and maintained effectively, maximizing their value and impact.
Addressing Challenges in Data Product Management
Implementing and managing data products is not without its challenges. One significant challenge is aligning the organization’s understanding of what constitutes a data product. Having a clear and aligned definition of data products across the enterprise is crucial for successful implementation.
Another challenge is ensuring that data products are integrated into the organization’s strategy and processes. This integration requires a robust data strategy that includes data products as a core component. It also involves establishing clear accountability and ownership for data products, ensuring they are supported and maintained throughout their lifecycle.
Organizations must also address the challenge of data quality. Ensuring that data products are based on high-quality data is essential for their success which requires robust data governance practices, including data quality assessments, data cleansing, and ongoing monitoring. By maintaining high data quality standards, organizations can ensure that their data products deliver accurate and reliable insights.
The Importance of Metadata in Data Products
Metadata plays a vital role in the management of data products, providing the necessary context and information about the data product, including its source, quality, and usage terms. Effective metadata management is crucial for the success of data products. As Steve Fisher, Principal Consultant, Ortecha Ltd, and one of the leads of the EDM Council data products working group, noted, “A data product is really a data resource with a lot of metadata around it to describe it.” Comprehensive metadata ensures that data products are well-documented and easily accessible, enhancing their usability and value.
Metadata helps users understand the origins, context, and quality of the data, making it easier to trust and utilize the data product. It also facilitates data discovery and access, allowing users to find the data products they need quickly and efficiently. By providing detailed metadata, organizations can ensure that their data products are transparent and trustworthy.
Furthermore, metadata plays a critical role in data governance. It helps organizations track data lineage, ensuring that data products comply with regulatory requirements and internal policies. Metadata also supports data quality management by providing information on data accuracy, completeness, and consistency. By maintaining comprehensive metadata, organizations can enhance their data governance practices and ensure that their data products meet high standards of quality and compliance.
Conclusion
Understanding and managing data products is essential for maximizing the value of data in the modern data landscape. By defining what constitutes a data product, differentiating it from data assets, and highlighting its role in data marketplaces, organizations can leverage data products effectively.
Implementing a lifecycle approach to data product management and addressing challenges such as alignment and integration are essential steps for organizations. The critical nature of data product discussions cannot be overstated, particularly when considering data marketplaces. Clear definitions, strategic alignment, and robust lifecycle management are key to successful data product implementation. Without a shared understanding, varying interpretations of what a data product is could lead to inconsistencies and inefficiencies.
As the industry continues to evolve, collaboration and continuous learning will drive better business outcomes and innovation in data management. By focusing on the critical aspects of data product management, organizations can ensure that they are well-positioned to succeed in the evolving data landscape.
Through dedicated efforts and a commitment to excellence, organizations can transform their data management practices and achieve significant advancements in data utilization and governance.
Learn More About EDM Council
- EDMWebinar: Designing and Managing Data Products (view recording and materials)
- Data Products and Data Marketplaces SIG (create a login to get involved)
- Data ROI Working Group (learn more and download published reports)
This quarter’s column contributed by:
Jim Halcomb, Head of Product Management, EDM Council
Jim Halcomb is Head of Product Management for the EDM Council. He is a strategy, data management, and cybersecurity executive with 30 years of international business experience. Jim has worked with the Council since its inception in 2005, eventually leading the initial research and development of the DCAM from late 2011 to 2014. Jim also leads the Council’s Special Interest Groups program, and is actively involved with the Data Products and Data Marketplaces group.
