1. Base DataViews & DataMart Architecture 2. CRM and Transactional Data 3. Data Security and Governance 4. Signposting of Insights 5. Metadata and Data Lineage 6. Master Data Management (MDM) 7. ETL/ELT and Data Integration Processes 8. Analytics and Data Modelling 9. Data Lifecycle Management & Archiving 10. Data Quality and Stewardship 11. Real-Time Data … Read more
Objective: Design, develop, deploy, and maintain Datamarts with a focus on performance, security, and usability. Steps: Data Discovery and Requirements Gathering Datamart Design and Security Planning MVP Development and Iteration Deployment and Go-Live Maintenance and Performance Testing
Objective: Efficiently acquire data from various sources and ensure secure, accurate, and timely transport to the data lakehouse and data warehouse. Steps: Data Source Identification and Mapping Data Profiling and Classification Data Acquisition and Integration Transport to Data Warehouse Testing and Validation
It is essential for BMT to take a holistic approach and adopt a combination of different strategies, such as Data Ops, Data Observability, Data Mesh, and Data Quality Checks to improve the quality of data. Despite the differences in focus, one common thing among the frameworks strategies above is the need for a unified governance … Read more
Standard Operating Procedures (SOPs) guide the DOM’s processes, ensuring efficiency and consistency at each stage. Purpose & Scope of the Data Operating Model Standard Operating Procedures Across Key Stages Data Planning SOPs Data Acquisition SOPs Data Processing & Maintenance SOPs Data Publish & Share SOPs Snapshot & Archive SOPs Data Flow and Governance within the … Read more
Data quality management within the DOM ensures that data remains accurate, consistent, timely, and reliable across the organisation. Accuracy How well does a piece of information reflect reality? Accuracy refers to the degree in which the data correctly portrays the real-world situation in which it was originally designed to measure. Data must be meaningful and … Read more
The DOM’s governance framework defines clear roles, policies, and responsibilities, ensuring data is trustworthy, compliant, and effectively managed across its lifecycle. Data Governance Structure: Establishes an oversight committee and data stewards across departments to maintain quality. Roles & Responsibilities: Assign data owners, stewards, and custodians to manage, validate, and secure data across departments. Quality Control … Read more
A Data Warehouse & Data Mart Operating Model alone does not create quality and value but requires an intersection of process, people, and technology conceived around the data model to provide its actual value. Building processes and organisational structures to deliver compelling data products to users is the realisation of what the Data Operations Model … Read more
Data Operating Model For BMT to remain competitive in a rapidly evolving technological landscape, it must be able to adapt quickly to insights and new developments. The modern enterprise data warehouse model within the DOM facilitates access to reliable, timely, and structured data insights, empowering informed decision-making. Key benefits include: Medallion Architecture To facilitate structured … Read more
The Data Operating Model (DOM) is designed to support BMT’s strategic objectives through a structured, high-quality data framework. It centralises, secures, and optimises data handling to enable agile, data-driven decision-making across BMT’s global operations. This model outlines how data is acquired, transformed, governed, and made accessible to provide a “single source of truth,” supporting consistent … Read more