The data management landscape is shifting, with a growing trend towards decentralized domain ownership. This approach involves domains taking control of their data products, from development to support, in an effort to improve data interpretation. The rationale behind this shift is that domains, being closer to the data sources and possessing relevant expertise, are better equipped to extract insights from their data.
However, this trend also presents several challenges. One major hurdle is the need for a significant organizational transformation, which can be difficult to implement. Some domains may resist the change, lacking the necessary incentives or knowledge to assume this new responsibility. Furthermore, the skills and expertise required to manage data effectively may not be evenly distributed across the organization.
From a technical standpoint, decentralizing data ownership also raises concerns about duplication of effort. If each domain develops its own solutions, it may lead to a fragmented technology landscape, with multiple, potentially incompatible systems. This could negate the benefits of decentralization and may not be more efficient than a centralized, highly skilled team.
To overcome these challenges, organizations need to find a way to empower domains to take control of their data without creating a skills and technology mismatch. This requires a thoughtful approach to structuring data ownership, ensuring that domains have the necessary resources and support to manage their data effectively. Additionally, it’s crucial to establish clear data and security governance standards to maintain consistency and ensure that data is handled responsibly.
Key Considerations:
Challenges in implementing decentralization:
Organizational transformation
- Lack of incentives or knowledge among domains
- Uneven distribution of data management skills and expertise
Technical concerns:
- Duplication of effort
- Fragmented technology landscape
- Incompatible systems
Overcoming challenges:
- Empowering domains with necessary resources and support
- Establishing clear data and security governance standards
- To achieve successful decentralization, organizations must:
- Balance domain autonomy with standardized data management practices
- Define the role of central data teams in supporting domains
- Establish and enforce data governance standards to ensure consistency and accountability
Major components of a multitenant data platform that provides self-service capabilities are:
Multitenant Kubernetes Developer Platform: This component allows multiple domains to develop and deploy their applications in a shared Kubernetes environment, providing a scalable and secure way to manage containerized workloads. The multitenant aspect ensures that each domain has its own isolated environment, while still sharing resources and infrastructure.
Common Data Services with Strict Data Access Management: This component provides a set of shared data services that support various data sources, such as a lakehouse, messaging systems, and databases. These services are designed to work together seamlessly, allowing data to be easily shared and integrated across different systems. The strict data access management policies ensure that data is accessed and used in a secure and governed manner, in compliance with organizational policies and regulations.
Paved Road Approach for Lifecycle Management and Data Product Technologies: The “Paved Road” approach suggests a pre-defined set of approved technologies and tools that are well-integrated and supported by the platform. This approach enables developers to focus on building data products without worrying about the underlying infrastructure and technology stack, making it easier to manage the entire lifecycle of data products, from development to deployment and maintenance.
Data Catalog for Easy Data Product Discovery: A data catalog is a centralized repository that provides metadata about the available data products, including their descriptions, formats, and usage guidelines. This component enables data consumers to easily discover and access relevant data products, making it simpler for domains to share and reuse data assets across the organization.