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
Purpose To help Data, Engineering & Analytics (DE&A) leaders assess current maturity across the five BHAG areas, identify natural strengths, and agree three actions to progress capability and culture. BHAG 1: Culture & Stakeholder Engagement Theme: How people use, trust, and talk about data and information. Ask: BHAG 2: Data Acquisition & Integration Theme: How … Read more
Purpose: Enable BMT to make informed, confident, and responsible decisions through trusted, accessible, and intelligent data. BHAG 1: Culture and Stakeholder Engagement Foster a culture where people, systems, and decisions are guided by evidence, shared understanding, and confidence in data and information. BHAG 2: Data Acquisition and Integration Build connected and reliable information flows across … Read more
This note explains how to turn the current views (wide–from–tall) into a report‑friendly table using Power Query (recommended) or DAX. It covers two common layouts: It also shows how to extract a human‑readable Description from the JSON in VALUE_METADATA. Source schema (tall, meta-driven) Expected columns: Assumption: Each (OBJECT_SEQ, [META_TYPE], ATTRIBUTE) appears at most once for … Read more
To ensure efficiency, compliance, and trust in the Data Warehouse, we commit to the principle of non-proliferation of information. This means that data will be held and processed in a way that avoids unnecessary duplication, ensures clear lineage, and retains only what is required for business and regulatory purposes. Standards This approach ensures the Data … Read more
1. Collaboration & Communication 2. Reliability & Delivery 3. Technical & Professional Expertise 4. Innovation & Improvement 5. Customer/Stakeholder Focus 6. Leadership & Influence (even without formal authority) 7. Personal Attributes
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
I thrive where challenge, novelty, and passion meet. I learn visually and by doing things myself. Engagement is key for me – if my brain isn’t bought in, it can’t focus on the task. Guide me with clarity of purpose, insight, novelty and challenge and I’ll deliver energy, creativity, and continuous improvement. 🧩 How I Work Best … Read more
I thrive at the intersection of curiosity, novelty, and real-world value, but I also perform best when work is structured, collaborative, and purposeful.Exploration and improvement energise me, yet clarity of expectations and harmony in the team keep me focused.Guide me with clarity of purpose, and I’ll deliver energy, creativity, and continuous improvement. 🧩 How I … Read more
🧾 Incident Summary: Discrepancies were identified between the Headcount report and the Management Accounts (MA) reporting figures. The headcount submission process also suffered from data entry issues, retrospective updates, and manual effort required to maintain alignment across periods. 🔍 Root Cause Analysis 1. Inconsistent Timing of Submissions 2. Differences in Ownership and Definition 3. Submission … Read more