Customer Journey Bible

Project Margin Variance Report – Requirements Specification

by

Version: 1.0Owner: Regional Finance DirectorPrepared by: Data Engineering 1. Purpose The purpose of this report is to provide clear and consistent visibility of margin performance across all active projects, comparing the originally approved bid margin with the latest forecast outturn margin. The report will support financial oversight, early risk identification, and commercial performance management at project, PRU, and regional levels. 2. Objectives 3. … Read more

Microsoft Fabric Deployment Pipelines

by

What are Deployment Pipelines? Pipeline Structure Stage Comparison in UI Item Pairing & Status Selective Deployment Deployment Rules Lakehouse & Deployment Pipelines in Fabric Deployment pipelines move Lakehouse metadata, including shortcuts, but do not copy data or table schemas. After deployment, shortcuts still point to the original source, and the Lakehouse will be empty unless … Read more

Data Integration Standard

by

Issued by: Data & Analytics TeamApplies to: All data integrations, pipelines, and views entering or leaving the Data WarehouseStatus: Approved DraftDate: [Insert Date]Version: 1.0 1. Purpose This standard defines the structure and principles for integrating data from source systems—including ERP (IFS), Dynamics 365, Power Apps, and SharePoint—into the enterprise Data Warehouse. It ensures that data … Read more

Architecture Rules of the Road

by

A calm, consistent, and clever approach to data engineering. 🔹 1. Look in the Box First Before inventing a workaround, check what already exists.If Microsoft or IFS built it, use it — it’s likely more robust, secure, and supported. 🔹 2. Easy Landings Data should arrive safely and predictably.Keep import containers simple, standardised, and transformation-free.Bronze … Read more

Playbook: DataMart & Reporting Development Process

by

This process explains how Data Engineering (DE) and Analytics Reporting (A) work together to turn a business need into a trusted, production-ready report. It’s designed for non-technical managers: no jargon, just what happens, who’s responsible, and what the outcomes are. Phase 0: Definition – Ground Zero PurposeLay the foundation before vision-shaping begins. Ensure clarity on … Read more

Case Study: Leading Technical Projects Without the Data Headaches

by

Role: Project ManagerContext: Large-scale technical consultancy engagement requiring coordination across engineering, finance, and delivery teams 🔪 Challenge The project manager needed to: Problems included: “I spent hours each week trying to make sense of data from five different places—and still couldn’t guarantee it was accurate.” 🚀 Solution The Data Engineering team: 🌟 Outcome “Now I … Read more

We build the data foundation so you can focus on delivering.

by

At the heart of every report, dashboard, and project delivery, there’s data—clean, consistent, and flowing on time. That’s what Data Engineering delivers. Whether you’re chasing a deadline, answering a tough question, or leading a major project—we make sure you have the data you need, when you need it. ⚖️ Clarity You get clean, reliable data … Read more

White Paper: Common Data Model (Datamarts)

by

Proposal for a white paper on Common Data Model (Datamarts) Proposed Structure for the White Paper 1. Executive Summary 2. Introduction 3. Objectives 4. Proposed Standardised Format 5. Naming Conventions 6. Standardised Structure for Views 7. Metadata Format 8. Implementation Roadmap 9. Benefits 10. Conclusion Naming Suggestions for Views Here are some options for naming … Read more