Project Organisation

People involved and their roles, chains of command and reporting methods, distribution list of SQP.

Data Steering Committee

• Business led, IT assisted.
• Holders of the decision rights for the governance policies enacted.
• Define goals, rules, and policies for the program.
• Approve, fund, and prioritise projects to address data and analytics needs.

Data Stewards

• Act as liaisons between the business and the D&A and IT teams.
• Enforce data and analytics governance policies and standards created by the steering committee.
• Manage and resolve deviations and exceptions to policies

Data Specialists

• Act as custodians and help with maintenance for specific data.
• Partner with data stewards to implement data transformations, resolve data issues and collaborate on system changes.

Quality Behaviours of Data Specialists

1. Leading and promoting a culture that values and protects data.
2. Knowing what data you manage and why.
3. Knowing who has access to the data whilst you are responsible for it and why.
4. Understanding and addressing risks to the data whilst you are responsible for it.
5. Ensuring the data is used efficiently and effectively to achieve your department’s and the BMT’s vision.
6. Acting as the nominated “owner” of an assigned data asset(s) on behalf of your department and the BMT.
7. Ensuring that the data is processed for purposes consistent with the strategic objectives of your department.
8. Determining how the data is collected, processed, retained and disposed of within your department in line with the overarching BMT framework; and
9. Working with other Data Specialists to collaborate on internal data sharing arrangements.

Data Engineering

• Develops and constructs data products and services (Data Marts),and integrates them into systems and business processes.
• Provides support for the development and maintenance of data analysis/analytics systems though Data Mesh Principles.

Data Mesh Principle

The Data Mesh decentralises data ownership by transferring the responsibility from the central data team to the business units that create and consume data.

By decentralising data ownership to domain teams, Data Mesh promotes agility, innovation, and accountability within BMT. It enables faster decision-making, facilitates collaboration across business units, and empowers domain experts to derive actionable insights from data more effectively.

Data Engineering operates on the principles of domain-driven design, product thinking, and federated governance.

Principle	Activity	So that…
Domain-oriented Decentralised Data Ownership and Architecture:	Implement data flows to seamlessly connect operational systems with analytics and business intelligence (BI) systems	domain teams can own and manage their data independently, fostering agility and innovation within their domains.
Data as Product:	Document clear source-to-target mappings for transparency and traceability	data is treated as a valuable product, ensuring that it is well-understood, curated, and accessible for consumption by domain teams.
Self-service Infrastructure as a Platform:	Provide a data developer portal (myBMT & Knowhow) Direct data access with Command GET and API services	domain teams can autonomously access and utilise data infrastructure and tools, enabling them to build, deploy, and manage data pipelines and applications without the need for extensive support from centralised teams.
Federated Computational Governance:	Provide support for the development and maintenance of data analysis/analytics systems (myBMT & Knowhow)	Best practice and computational learning can be distributed, allowing domain teams to govern their data processing and analytics workflows according to their specific needs and requirements.