A practical classification standard for reusable data views Purpose This taxonomy provides a consistent way to classify tables/views within the Common Data Model (CDM). It separates: The goal is clarity, scalability, and predictable design across domains such as Order, Project, Employee, Invoice, Customer, and Person. 1. Core Principle Core identifies, Meta describes, Item records, Event … Read more
1. Purpose This guide shows how to build a Power BI report using the standard DataMart wireframe. It demonstrates how: The wireframe is not just a template — it is a working example of how reporting should be built. 2. The Principle Engineering defines the data.Analysts define the question.The wireframe allows both to operate without … Read more
This process describes how to take a new data source from landing → Bronze → DataMart view, and fully define its attribute lineage in myBMT. 1. Prepare and review the new data source 2. Catalogue and land the source 3. Plan the DataMart view(s) 4. Set up attribute lineage in myBMT For each new view … Read more
Should We Reuse Standard Dynamics 365 / Dataverse Tables for Our In‑House Apps? 1) Why We’re Talking About This We’re starting an important conversation: when we build apps internally, should we lean on the standard tables already in Dynamics 365 / Dataverse (like Account, Contact, Opportunity, Project), or should we keep spinning up new SharePoint … Read more
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Purpose This playbook guides the phased migration from existing DataMart views (202409) to CDM-standard views, including core, meta (dates, codes, values), and item tables. It supports the transition to IFS Cloud and ensures a consistent, scalable data model across all domains. MVP Scope Domains required for MVP: Phased Delivery Approach Phase 1: Live Data Seeding … Read more
🎯 Purpose This framework ensures that values in complex metadata structures (e.g. project earned value, invoice accounting, or employee attributes) are verified for presence even when using incremental loads. It protects against stale data persistence or silent value loss, using metadata-driven auditing. 🧩 Problem Context In many CDM views, values are upserted using procedures like … Read more
🎯 Objective To proactively expire or flag metadata rows that are no longer present in the source data even if their values haven’t changed, avoiding persistence of stale or misleading data. 1. 🏗 Recommended Table Extension Add these optional columns to any table using patch_upsert or put_update: 2. 📥 Staging Input Table – stage.project_values_current Your … Read more
🎯 Core Issue: 🔍 Risks of the Current Approach Scenario Problem Value disappears entirely You keep the last-seen value forever unless a new version overwrites Value moves to another key The old one is retained, and the new one appears as duplicate context Periodic reporting gaps Reporting shows a “stale” value that’s no longer present … Read more