Effective change management depends on clear ownership, timely decisions, and coordinated delivery. Delays are often caused less by technical complexity and more by uncertainty over who is responsible for action. This page defines the typical roles involved in managing changes across data, reporting, and analytics services. The objective is to ensure requests are progressed efficiently, … Read more
The Emergency Change Route provides a controlled mechanism for implementing urgent changes where waiting for the standard delivery cycle would create unacceptable business risk. Emergency changes are exceptions to the normal change process. They should be used sparingly, assessed quickly, and managed with discipline. Urgency alone does not automatically qualify a request as an emergency. … Read more
This area defines how changes to data, reporting, and analytics services are requested, assessed, delivered, and communicated. Effective change management protects trusted outputs while enabling continuous improvement. It ensures low-risk improvements can move efficiently, while higher-risk changes receive the appropriate level of review, validation, and visibility. The objective is simple: deliver change with confidence, clarity, … Read more
This page provides the formal record of recently delivered changes across data, reporting, and analytics services. It is the primary reference point for understanding what has been released into service, what assets were affected, and whether any user awareness or follow-up action is required. All users, analysts, and support teams should use this page as … Read more
Continuous improvement depends on clear, well-defined change requests. Whether the request is a small enhancement, a logic correction, or a larger structural improvement, good change information allows the right people to assess, prioritise, and deliver efficiently. Poorly defined requests create delay, rework, and misunderstanding. Well-raised changes move faster. This guide explains how to raise a … Read more
Changes to data, reporting, and analytics services vary significantly in complexity and risk. Some are simple service improvements. Others may affect trusted figures, operational decisions, or access to sensitive information. To support timely delivery while maintaining confidence, changes should follow a route proportionate to their impact. This matrix helps classify requests consistently and select the … Read more
Modern reporting environments need to improve continuously. New requirements emerge, defects are identified, source systems evolve, and opportunities to simplify or optimise are found every week. Not every change carries the same level of risk. Changing a label on a report is not the same as changing revenue logic. Improving performance is not the same … Read more
How data is structured, governed, and consumed across the organisation 1. Purpose To provide a stable, governed data platform that: 2. Core Principle Data is not delivered as tables — it is delivered as structured, governed objects with defined behaviour 3. Platform Structure 3.1 Canonical Data Model (CDM) The platform is built on a consistent … Read more
Managing Dataflow Gen2 across multiple environments (Development and Production) can be a headache. By default, the destination Lakehouse or Warehouse IDs are hardcoded. This means when you deploy to a Production workspace, your dataflow might still try to write back to your Development environment. In this guide, I’ll show you a workaround to parameterize your … Read more
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