Release 80

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DataMart views changed since 01-Oct-2025. Executive summary New views Renamed / globalised Downstream dependencies: Corrections Improvements to source identification & aliasing Purpose: Ensure tables are identified using their non-dollar names for lineage and metadata consistency. Change pattern:'{“Source”:”ifs.[QFACT_BMT_DWH_INVOICE_TAB_IAS$]”}’ as SOURCE_SYSTEM→'{“Source”:”ifs.[QFACT_BMT_DWH_INVOICE_TAB_IAS]”}’ as SOURCE_SYSTEM Views updated: Global query structure change (Beta & 202409 queries) Adopted a consistent CTE … Read more

Running a Stored Procedure for Multiple Dates in Power BI

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Purpose:To run the stored procedure get.myArchive from Power BI for a series of previous Sundays (for example, the last six Sundays), and optionally combine or parameterise the results. 🧭 Background The get.myArchive procedure is designed to retrieve snapshot data for a specified date.By default, Power BI passes a single date parameter such as: However, when … Read more

Data Integration Standard

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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

Project.Meta_Codes_PMN

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Project Managers Narrative Purpose This view supports a range of portfolio and project management insights, helping decision-makers understand delivery health and emerging risks across all active projects. It transforms Project Manager Narratives (PMNs) into a structured, analysable format, making it easier to identify recurring risks, schedule pressures, and delivery challenges. By standardising how commentary is … Read more

Feedback.Meta_Satisfaction

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Purpose This view brings together customer feedback from multiple sources into a single, consistent structure — helping teams understand satisfaction trends, sentiment, and consent status across the customer journey. It supports unified reporting of Net Promoter Score (NPS), customer comments, and response context (such as project or milestone), giving a clear view of how customers … Read more

Person.Meta_Codes_SkillsBase

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Purpose This view supports workforce capability management and planning by providing consistent, up-to-date insight into employee skills, certifications, and team structures. It enables HR, project managers, and business leaders to make better decisions about deployment, development, and compliance. Use Case Suggested dashboard insights: Source Primary Source(s): Load Path SkillsBase API (2FactAuth) → (ADF Pipeline) → … Read more

Employee.Meta_Codes_SkillsBase

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Purpose Produces attribute‑level metadata for people and skills sourced from skl.people and augmented with IFS person/employment lookups. Attributes include EMAIL, ID, TEAM_ID, ROLE_ID, LOCATION_ID, DOMAIN, and recent assessment dates. The view follows the CDS object + meta_codes pattern: the item is the Employee object and each row represents a single coded attribute/value, normalised for downstream … Read more

Template.DataMart

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<Domain.Object_ViewName> Template note: Replace all <placeholders> with your content. Keep sections, even if marked “N/A”, so views stay consistent across the Common Data Standard (CDS). Purpose A concise paragraph stating why this view exists and how it aligns to the CDS item & values table pattern. Mention the primary decision/use it supports. Example prompt: “This … Read more

Architecture Rules of the Road

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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

BHAGs: Diagnostic Questions

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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