BHAG3: Develop a Data Literacy Pathway Leading to a Wrangler Academy
Start-up: Foundation: Reporting: Predictive: Embed:
Governance & Leadership
BHAG2: Deliver Sustainable, Accessible Data Products as a Single Source of Truth
Start-up: Foundation: Reporting: Predictive: Embed:
BHAG1: Embed Data-Driven Culture Across All Operations
Start-up: Foundation: Reporting: Predictive: Embed:
Foundational Principles for Data Engineering in Support of the BHAGs
Data Engineering is a crucial enabler for BMT’s data transformation goals. The following principles define the scope and commitments of Data Engineering to support our broader strategic aims: Conscious Design Promote forward thinking around usability and interoperability of the data and user-centric design principles of sustainable data products Purpose-Driven Platform: The modern data platform is … Read more
Revolutionise Data Infrastructure
Aim to completely transform the data infrastructure of the organisation, making it agile, scalable, and highly efficient. This could involve implementing cutting-edge technologies like distributed computing, real-time processing, and machine learning pipelines.
Zero Downtime Data Systems
Set a goal to achieve zero downtime for data systems. This would involve building robust redundancy, fail-over mechanisms, and automated recovery processes to ensure continuous data availability.
Data Democratisation
Strive to make data accessible to everyone in the organisation, regardless of technical expertise. Implement self-service analytics tools, intuitive dashboards, and comprehensive data documentation to empower all stakeholders to make data-driven decisions.
AI-Driven Data Operations
Work towards implementing AI and machine learning algorithms to optimise data operations. This could involve automating data quality checks, anomaly detection, and predictive maintenance for data infrastructure.
Scalable Data Processing
Set a goal to build a data processing pipeline that can effortlessly handle massive volumes of data without any performance degradation. This could involve leveraging technologies like Apache Spark, Apache Flink, or Google Dataflow to achieve seamless scalability.
Real-Time Analytics
Aim to enable real-time analytics capabilities for the organisation, allowing stakeholders to make decisions based on the most up-to-date information. This could involve building streaming data pipelines, implementing complex event processing systems, and developing real-time dashboards.