In the rapidly evolving landscape of enterprise data management, a significant shift is underway. Organisations are moving away from traditional, centralised data warehouses toward a more flexible, product-oriented approach to data. This transformation isn't just a technical evolution—it represents a fundamental rethinking of how businesses create value from their data assets.
The Evolution from Data Warehouses to Data Products
For decades, enterprises have relied on centralised data warehouses as the backbone of their analytics infrastructure. While these systems have served their purpose, they often struggle with the volume, variety, and velocity of data that modern businesses generate. Gartner's 2025 data and analytics report emphasises the importance of highly consumable data products. They recommend that data and analytics leaders focus on creating reusable and composable data products to address data delivery challenges and enhance user experience.
What Are Data Products?
Data products represent a paradigm shift in how organisations package, share, and consume data. Unlike traditional data assets, data products are:
Self-contained: They include not just data but also the metadata, documentation, access controls, and quality metrics needed to use them effectively
Purpose-built: Designed with specific business outcomes in mind
Discoverable: Easily found and accessed by those who need them
Trustworthy: With clear ownership, lineage, and quality indicators
McKinsey emphasises that curating data into rich, multipurpose, dynamic data products minimises data engineering efforts and enables high-impact use cases, thereby maximising time to market and return on investment. They also highlight the shift from siloed data management to dedicated teams overseeing data products, which enhances data security and facilitates self-service access and analytics.
Real-World Transformation Success Stories
The shift to data products isn't just theoretical—leading organisations are already reaping the benefits:
Global Financial Services Leader
A Fortune 500 financial institution transitioned from an on-premises data lake to a cloud-based platform using Snowflake. This shift enabled the company to pull key reports daily—down from once a week—and provided a framework to expand data accessibility. The transition also led to automated quality assurance and validation during data ingestion, resulting in operational cost savings.
Healthcare Innovation
A healthcare solutions provider serving over 90 million members aimed to standardise their Power BI dashboards across 149 departments. By implementing uniform design standards and templates, they achieved:
40% reduction in dashboard creation and update times.
50% decrease in dashboard creation time through the use of reusable templates.
35% reduction in navigation errors, enhancing user experience.
Addressing Data Complexity Through Product Thinking
Modern enterprises face unprecedented data complexity. This complexity creates significant challenges, such as:
Data duplication and inconsistency
Governance and compliance risks
Difficulty finding and accessing relevant data
Lengthy time-to-insight for business users
Data products directly address these challenges by encapsulating complexity and presenting data in business-ready formats. By packaging data with its context, controls, and consumption interfaces (like Power BI dashboards), data products dramatically simplify the user experience.
Additionally, a report by Edge Delta reports that the global data analytics market was worth $49.03 billion in 2022, indicating significant investments in data management solutions.
The AI Imperative for Data Products
Perhaps the most compelling reason for the shift to data products is the rise of AI and machine learning. IDC's 2025 FutureScape report indicates that 67% of the projected $227 billion AI spending in 2025 will come from enterprises embedding AI capabilities into their core operations, surpassing investments in leading cloud and digital service providers.
However, AI initiatives face a common obstacle: access to high-quality, trusted data. For instance, this report by IBM states that 25% of enterprises exploring or deploying AI cite excessive data complexity as a barrier to successful AI adoption.
Introducing Keyrus Data Marketplace: Enabling the Data Product Revolution
Recognising the critical need for effective data product management, Keyrus has developed an innovative data marketplace solution that addresses the key challenges organisations face when transitioning to a data product approach.
Platform-Agnostic By Design
Unlike vendor-specific solutions from Snowflake, Databricks, or Starburst that create lock-in, the Keyrus Data Marketplace is platform-agnostic, allowing organisations to catalogue and share data products regardless of where they reside.
Distinctive Capabilities
The Keyrus Data Marketplace stands out with several key capabilities:
Enhanced Shareability: Facilitates a decentralised yet interoperable architecture, enabling teams to share data products across organisational boundaries while maintaining governance and security.
Strengthened Governance: Improves data product governance through automated quality checks, comprehensive lineage tracking, and granular access controls—essential for building trust in data assets.
User-Centric Design: Encourages active participation from data consumers, ensuring data products evolve to meet real business needs rather than remaining static assets.
Multi-Tenant Architecture: Delivers a white-labelled experience for different business units or external partners, with customised branding and access controls.
AI-Enhanced Discovery: Leverages generative AI to transform how users find and interact with data products, moving beyond basic search to natural language interfaces.
Measurable Impact
Organisations implementing the Keyrus Data Marketplace have achieved significant benefits:
Streamlined Intake Process
Data product registration and approval workflows are 40-60% more efficient
Improved Data Quality
Issues are identified and resolved 75% faster through automated monitoring and user feedback mechanisms
Expanded User Base
Typical deployments see a 3X increase in active data consumers within six months
Enhanced Visibility
Executives gain a clear view of data platform utilisation and maturity through comprehensive dashboards
Looking Ahead: The Mobile Future of Data Products
Keyrus is already looking beyond the desktop experience to the next frontier: mobile data product access.
Our vision is to allow users to converse with data products, share insights, and manage data issues wherever they are. Imagine getting an alert about an important data change, reviewing it on your phone, and sharing it with colleagues—all without returning to your desk. For organisations feeling overwhelmed by data complexity or struggling to deliver value from their data investments, the shift to data products represents a critical strategic opportunity.
Additionally, Forrester's 2024 predictions for data and analytics emphasise the increasing significance of AI and data governance in organisations. They anticipate that nearly a third of chief information officers at large enterprises will collaborate with chief data officers to drive AI-powered business growth. Furthermore, 40% of regulated companies are expected to integrate their data and AI governance programs to ensure alignment with business objectives and regulatory requirements.
Ready to transform your organisation's approach to data? Contact Keyrus today to learn how our Data Marketplace solution can accelerate your journey from data chaos to data products.
Also discover Data Products Decoded: Your Guide to Choosing the Right Transformation Partner.