> For the complete documentation index, see [llms.txt](https://au-dohp.gitbook.io/au-dohp-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://au-dohp.gitbook.io/au-dohp-docs/faqs.md).

# FAQs

**1. What is AU-DOHP, and how does it solve data governance challenges?**\
AU-DOHP leverages the Data Mesh concept by decentralizing data ownership. It distributes data responsibilities to domain teams rather than relying on a central team. This decentralization allows teams within human, animal, and environmental health domains to independently manage and analyze their data, enabling cross-domain integration, much like how APIs work in a microservice architecture.

**2. How does AU-DOHP improve data-driven decision-making?**\
AU-DOHP enhances data-driven decision-making by decentralizing data ownership and enabling self-service capabilities. This approach eliminates bottlenecks caused by a central data team, allowing domain teams to generate insights faster. As a result, decision-makers can access real-time data, improving overall agility and competitiveness across health sectors.

**3. How does AU-DOHP compare to a traditional centralized data system?**\
Traditional centralized data systems, like a data lake, consolidate all data into one repository, requiring a dedicated team for management and processing. This can create bottlenecks, slowing down decision-making. AU-DOHP, on the other hand, uses the principles of Data Mesh to decentralize data ownership. Each domain team manages its own data products, ensuring faster insights while maintaining interoperability through standardized governance, ensuring seamless data sharing across sectors.

**4. What are the required input and output formats for data pipelines?**\
The mandatory requirement is to have a "Parquet File Output" transform that adheres to predefined settings. There are no additional format restrictions.

**5. Are there limitations on pipeline complexity or execution time?**\
No, there are no limitations on pipeline complexity or execution time. However, performance may vary based on the server configuration.

**6. How are data contract schemas managed and updated over time?**\
Data contract schemas can be updated post-creation and support versioning.

**7. Can multiple versions of the same data contract be used simultaneously?**\
Currently, this feature is not supported but is planned for future releases.

**8. What happens when a data contract is modified?**\
Currently, there are no constraints, but future platform updates will validate modifications against all associated data products.

**9. How does AU-DOHP handle data product access control?**\
Access to a data product must be explicitly requested. There is no direct access inheritance from data contracts.

**10. How are data product updates handled?**\
Metadata versioning is supported, but data product outputs are overwritten when the underlying data changes.

**11. What are the different data product access levels?**

* **Private:** Visible only to the owner.
* **Team Only:** Accessible only to team members.
* **Public:** Visible to all but requires explicit access requests for data usage.

**12. How does the platform enforce data contract constraints?**\
The enforcement is automated. Validation checks ensure compliance with schema and quality requirements whenever data changes.

**13. Does AU-DOHP provide data usage logs and audit trails?**\
Yes, data owners can view and manage access logs in the Governance tab.

**14. Are there notifications for data access requests?**\
Currently, data owners receive email notifications for access requests. A real-time notification feature is under development.

**15. Does AU-DOHP provide analytics on data usage?**\
Yes, users requesting data access must specify the purpose, and future updates will include analytics on usage patterns.


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