Every organisation wants faster, more trusted information, but the path from transactional systems to dependable insight is crowded with technical choices. Warehouses, lakes, streaming tools and vendor-specific ERP reporting layers overlap, and without a clear strategy teams build duplicate pipelines, argue about definitions and carry growing platform costs. Leaders need both the vision to prioritise and the engineering fluency to judge what is feasible.

This advanced programme joins strategic planning with applied engineering. In the first half, participants examine data strategy and operating models, then work through database design, query performance, data modelling for analytics and the structure of ERP data in common platforms. The second half moves to modern practices: building and orchestrating batch and streaming pipelines, designing lakehouse and warehouse layers, applying quality tests and lineage, and setting governance that supports self-service without losing control. Innovation sessions show how to scope pilots, evaluate new technologies, treat datasets as products and track value.

Participants spend much of each day in labs with sample ERP, operational and event data. They compare architecture options, build working pipelines, and develop a strategy document with roadmap, team structure and business case that they can put before senior management on return.

By the end of the course, participants will be able to:

• Develop a data engineering strategy and roadmap tied to business priorities.
• Compare architecture patterns such as warehouse, lake, lakehouse and data mesh and select suitably.
• Design and tune relational and NoSQL databases for transactional and analytical workloads.
• Extract, model and reconcile ERP data from finance, procurement, inventory and HR modules.
• Build and orchestrate batch and streaming pipelines with testing and monitoring.
• Implement data quality rules, lineage, master data and access governance.
• Manage cloud platform cost and performance.
• Plan and evaluate innovation pilots and data products.

The course is intended for technical leaders and senior practitioners, including:

• Data engineers and analytics engineers moving into lead roles
• Database administrators and architects
• ERP functional and technical consultants
• Business intelligence and reporting managers
• Heads of data, IT directors and chief information officers
• Enterprise and solution architects
• Digital transformation managers in banks, telecoms and manufacturing
• Government ICT and e-services leads

Participants leave the course with:

• A draft data engineering strategy and three-year roadmap.
• A reference architecture for their organisation's data platform.
• Working pipeline code and tests built in the labs.
• An ERP data extraction and reconciliation approach.
• A data quality and governance rulebook template.
• An innovation pilot canvas with success measures.
• A business case outline for platform investment.

The programme balances decision-level discussion with extensive technical practice. Participants will experience:

• Architecture workshops comparing options against realistic constraints
• Daily labs on SQL, pipeline tools and sample ERP and event data
• Code and design reviews that build habits of testing and documentation
• Case discussions of platform migrations and what went wrong
• A final project presented to a mock steering committee

Participants who attend the programme and complete the labs and final project receive a CPD-accredited Certificate of Completion issued by Vision Reach Global Consultancy.

The certificate records both the technical practice and the strategic planning work completed over the ten days.