Data Mesh Origins and Principles
In 2019, Zhamak Dehghani proposed the data mesh as a response to the failures of the classic data warehouse. Her critique highlighted persistent problems with a centralized approach including poor data quality, the failure to provide meaningful analysis and the high costs associated with these efforts.
She sought to consolidate the most successful practices she observed at her clients, and proposed four principles in a new way to organize the data function calling it the Data Mesh:
- Domain Ownership of Data – pushing data ownership to the source to manage data quality.
- Data as a Product – creating product ownership with clearly defined output and value measured by it’s usage downstream.
- Self Service Data Platform – allowing data product teams and their users to access and utilize data without going through a central team.
- Federated Computational Governance – reducing the need to move data and utilize it where it originates.
Her ideas struck an immediate chord, and much has been said on the topic since. And while Coginiti evolved independently of the data mesh, there is much in common with our thinking and Coginiti Enterprise is a data mesh operating platform for those seeking to implement a data mesh architecture.
The Data Mesh Operating Platform
The Coginiti data mesh operating platform provides a unified layer to manage and process data across all an organizations data, including all the major cloud and on-premise data platforms, data lakes and any SQL database. Coginiti leverages the local processing capability of all these platforms and provides a collaborative environment loved by data engineering and data consumers alike.
Key Capabilities
- Comprehensive Data Product Management: Coginiti enables teams to develop data products that include product documentation, reusable analytics, transformation code definitions, and data quality tests. This ensures that data products are reliable, up-to-date, and meet organizational standards.
- Version Control and Deployment: With Coginiti, data products are versioned and deployed in a governed manner, allowing for traceability and consistency in data operations and analytics across the organization.
- Integrated Catalog and AI Assistant: Coginiti’s catalog provides a trusted source for data products and higher order analytics alike. Through seamless connections to the query environment, discovery and AI assistant, users get the right assets at the right time.
- Collaboration: Engineers and Analysts work in the same environment, facilitating seamless collaboration. Coginiti’s editor also supports simultaneous peer editing, embedded commenting, code review and an easy process for sharing data assets.
- Industry Leading Platform Support: The platform boasts native compatibility with over seventeen data platforms an open connection to any SQL data store, and direct access to object storage across all major cloud providers, ensuring flexibility and broad applicability.
- Federated Governance: Coginiti integrates seamlessly with enterprise identity and access management systems, enabling efficient user provisioning and secure data platform connections. This integration ensures that data governance is maintained without sacrificing ease of access and usability.
Benefits of Coginiti in a Data Mesh Strategy
The rich feature set of the Coginiti platform provide comprehensive support for a data mesh strategy in a package which is easy to use, and fast to implement.
- Decentralization: Coginiti’s thin layer supports the decentralization of data, empowering data teams to manage their data products independently and reducing the reliance on a central engineering function.
- High Quality Output: Coginiti’s built-in data testing and governed publishing process catches errors before they reach the business and ensures consistency for critical business analysis.
- Reduced Data Platform Expense: By utilizing data assets where they lie, Coginiti reduces the large time and expense of moving data from one platform to another.
- Self-Service Infrastructure: Working directly with the query experience, The Coginiti AI assistant and discovery engine empower users across the organization top utilize data.
- Governance at Scale: Coginiti’s tight integration with an organizations security and identify management ensures that data governance is not compromised in the pursuit of accessibility and self-service capabilities.
Conclusion
By leveraging Coginiti’s comprehensive features and capabilities, organizations can effectively implement a data mesh strategy that promotes autonomy, enhances collaboration, and maintains stringent governance standards. Coginiti not only simplifies data management across diverse teams and platforms but also ensures that data is a reliable, scalable, and governed asset within the organization.
Contact Us
To learn more about how Coginiti can transform your organization’s data strategy, contact us at info@coginiti.co
