general
90 TopicsMicrosoft Fabric Tech
Microsoft Fabric is changing the way we think about modern data engineering. Instead of stitching together separate tools for ingestion, transformation, storage, orchestration, governance, and reporting, Fabric brings the entire workflow into one unified ecosystem. A typical Fabric data engineering journey can look like: πΉ Ingest data using Data Pipelines, Dataflows Gen2, or streaming πΉ Store and organize it in OneLake and Lakehouse πΉ Transform at scale with Spark, SQL, and Notebooks πΉ Orchestrate workflows with Data Pipelines πΉ Serve trusted data through Power BI and semantic models πΉ Monitor, govern, and deploy using Monitoring Hub, Purview, Git, and deployment pipelines The interesting part isn't any single feature β it's how naturally these components work together across the complete data lifecycle. OneLake underneath. Multiple workloads on top. One connected data platform.76Views0likes1CommentStacked Column Chart Data Limit Issue
I am encountering an issue with a stacked column chart in Power BI. Even though my data source only contains 200 rows, I'm still seeing the "i" icon (indicating a data limit issue). My x-axis shows phases, and my y-axis represents indexes (used as the legend to create the stack). I need the columns to be stacked as they currently are, but I'm unsure why this error is occurring with such a small dataset and how to resolve it.Solved13KViews4likes7CommentsArchitecture Patterns for Healthcare Data Platforms on Fabric
Architecture patterns for healthcare data platforms include building unified data foundations in Microsoft Fabric, where unified data is foundational to scaling AI effectively and Microsoft Fabric simplifies the analytics stack and accelerates time to value. What to include: Bronze β Silver β Gold Lakehouse layers Medallion architecture for clinical data Security boundary using Fabric Workspaces193Views0likes1CommentHealthcare Semantic Model
Hello all, I have been having some difficulty trying make the most efficient semantic model I can for my report. I'm finding a classic star schema to be challanging due to the content of my data. I'll do my best to summarize the organization of the data, in hope it can generate some ideas. General list of tables: Person_MRN (MRN as PK and Person_ID as FK) Person (Person_id as PK and wider table about the person) Condition_occurrence (features Person_ID, Visit_occurrence_id, diagnosis vist info) procedure_occurrence (features Person_ID, Visit_occurrence_id, procedural vist info) visit_occurrence (visit_occurrence_id as PK and care_site_id as FK) care_site (Care_site_id as PK) The design of my report is just to identify the distinct count of MRN with a filter selected condition and/or procedure, and the care site breakdown of those meeting the filter requirments. I am asking to map MRN -> condition_occurrence.person_id -> visit_occurrence.visit_occurrence_id -> Care_site.care_site_name but I also need MRN -> procedure_occurrence.person_id -> visit_occurrence.visit_occurrence_id -> Care_site.care_site_name since patients have more than one condition and/or procedure, I have to map through the visit_occurrence_ID's in order to capture the unique visits. There could even be a case where a distinct MRN with a distinct procedure was seen at more than one care site. I tried to make views to coalesce the information, but I haven't found the perfect fit yet. Any thoughts are appreciated!Solved19KViews3likes3CommentsAgent skills for Fabric CLI
As I've been working on efficiently using the Fabric CLI with coding agents (GitHub Copilot, Codex), I've come up with the following repo. In this repo, I created skills that you can install locally, and your coding agent can pick them up depending on the context. For example, if you want to get details about a recent failed pipeline, you can ask your agent: "What was the cause of my pipeline 'bronze_load' in the playground workspace?" It will automatically pick up the fab-job-ops skill and dig into the root cause of the pipeline's failure. Under the hood, it uses the Fabric CLI. For installing all necessary dependencies, see the README of the repo. The simplest way is to clone the repo and install the skills first. After that, use the fab-bootstrap skill to install the Fabric CLI and authenticate against Fabric. From there on, itβs only up to your imagination what you want to create. For example, you could say: "Create a logistics workspace attached to my capacity and generate dummy data. Create bronze, silver, and gold schema." There are also conventions baked in, such as naming conventions for folders, items, columns, and more. Additionally, when modeling a semantic model, several common best practices are already included. GitHub repository: dc-floriangaerner/fab-cli-skills6.9KViews1like1CommentIdea: Box and Whisker or Violin Plot Visuals as Standard Visuals
While there are third-party visualizations for Box and Whisker or Violin Plot visuals, some organizations don't allow the installation of third-party sources. Box and Whiskey or Violin Plot are very useful for understanding the mean, upper/lower quartile, and the max/min values of a dataset. Example might be HEDIS quality performance, BMI, paid per procedure -- all to better understand clinical variation in the community and within medical service centers. Box and whisker plots are frequently used visualizations in academic literature.9.1KViews3likes3CommentsDatacomplexity
Hello! I am new to Power BI and trying to do somethign quite complicated - or so I believe. I have two columns, one with let's say 'numbers X'. I have another column with let's say 'numbers Y'. I would like to return all X values with the same Y value for selected values in column 'numbers X', but not returning a repeat within a selected value from 'numbers X'. The issue I am running into is the lookup function is returning a repeat selected value for itself. See example below. '1' and '2' would be returned because it was found with same 'numbers Y'. '4' would not be returned because 'numbers Y' did not have a repeat value outside of itself.581Views0likes0Comments- 346Views0likes0Comments