Release Date: 18 November 2025 Overview This release introduces a number of improvements across customer, supplier, order, employee, and project data. Most updates focus on strengthening data quality, improving historical accuracy, and preparing for future Common Data Model (CDM) enhancements. No breaking changes are expected for reports. Key Improvements 1. Better Employee and Person Data … Read more
Release Notes – Week Ending 10 November 1. Feedback Meta Views Files: Summary:The former feedback_meta_codes_satisfaction view (over 800 lines) has been decomposed into its logical components to improve maintainability and clarity. These sub-views—covering Customer Voice, Customer Thermometer, Legacy External, and Legacy Internal—are now individually managed and combined through the new feedback_meta_satisfaction UNION view. This marks … Read more
Overview The cdm_Archive_to_STG notebook is a critical component in the cdm_today and cdm_Archive pipeline. Its primary role is to create a staging table that represents a point-in-time snapshot of source data, which is then used by the cdm__Archive_upsert notebook to accurately update the main dimension table. This staging layer acts as a buffer between raw … Read more
Overview The myOSH_To_Bronze notebook is designed to handle multiple MyOSH API endpoints dynamically, meaning it can process different endpoints such as records or users without hardcoding logic. For most endpoints (like users), the process is straightforward: it performs a regular API call and writes the response directly to JSON in the source container and to … Read more
Overview The myosh_Archive notebook is designed to maintain a complete and accurate archive of records from the MyOSH API. It ensures that no data is lost by identifying gaps in the current API response and backfilling missing records, then merging everything into a single, consolidated archive stored in the Azure Data Lake container. Why Do … Read more
Overview The cdm__Archive_upsert notebook is designed to help keep accurate historical records of data. It implements a technique called Slowly Changing Dimension Type 2 (SCD2), which means instead of overwriting old information, it creates a timeline of changes so you can see what was true at any point in time. This method ensures that previous … Read more
When working with Microsoft Fabric, one common challenge is keeping the SQL endpoint in sync with the Lakehouse endpoint after a pipeline run. Fabric provides two endpoints for every Lakehouse: Why does the SQL endpoint sometimes lag? The SQL endpoint doesn’t automatically refresh its metadata the moment new data lands in the Lakehouse. Instead, a … Read more
SharePoint list → cleaned, flat, ISO-dated table A reusable Power Query (M) snippet for Dataflows Gen2 that: When to use: Landing SharePoint list data into a Bronze/Silver layer (Fabric/Synapse/SQL) where flat, predictable schemas, text-formatted dates, and stable column names are preferred. Full code (drop-in) Step-by-step Customisation points Validation checklist Troubleshooting Notes
Weekly Release Note – Week Ending 03 November 2025 New Views project_meta_codes_pmn A new DataMart view based on data sourced from the SharePoint List PMN, processed via a GEN2 Dataflow to the Bronze layer.🔗 View Documentation This view enables portfolio and project management insights by transforming Project Manager Narratives (PMNs) into a structured, analysable format. … Read more