Press "Enter" to skip to content

Category: Microsoft Fabric

Dealing with the Lack of Identity Columns in Microsoft Fabric

Published 2024-10-14 by Kevin Feasel

Nikola Ilic forges a new identity:

If you’ve ever worked with traditional relational database management systems (RDBMS) and/or data warehouses, and you’re now trying to be a “modern data platform professional” and apply your skills in Microsoft Fabric, you may find yourself in uncharted territory. Not only because of the SaaS-ification of the environment, but also due to many puzzling “solutions”, or maybe it’s better to say – lack of the features that we were taking for granted in the “previous” (pre-Fabric) life.

The goal of this article is to introduce you with different approaches for overcoming the limitation of non-existency of the identity columns in Microsoft Fabric. Please keep in mind that all of these approaches are considered workarounds and it may happen that Microsoft in the future provide the out-of-the-box solution

Missing the identity column attribute can be a bit annoying when building out dimensions, so Nikola provides a few tips on how to emulate this functionality.

Comments closed

Invoking a Fabric Data Factory Pipeline from a Parent Pipeline

Published 2024-10-14 by Kevin Feasel

Andy Leonard takes us through a design pattern:

In an earlier post, I demonstrated one way to build a basic parent-child design pattern in Fabric Data Factory by calling one pipeline (child) from another (parent). In this post, I modify the parent and child pipelines to demonstrate calling a child pipeline that contains a parameter. In this post, we will:

  • Clone and edit the child pipeline
  • Clone and edit the parent pipeline
  • Test

Read on to see how it works.

Comments closed

Tips for Orchestrating Fabric Notebooks

Published 2024-10-14 by Kevin Feasel

Stepan Resl talks orchestration:

Let’s start by introducing what orchestration is and why it’s important to talk about shared resources. Orchestration is a discipline focused on managing and coordinating individual items or control elements to collectively manage the flow of our data operations. In the context of Fabric, this involves managing notebooks, dataflows, pipelines, stored procedures, semantic model updates, and many other items, activities, and services that may even be outside of Fabric.

Read on for some of the options, how they work in Microsoft Fabric, and tips for success.

Comments closed

Cloud Connections in Microsoft Fabric

Published 2024-10-10 by Kevin Feasel

Dennes Torres makes a connection:

I wrote about cloud connections when they were in a very early stage.

Cloud connections evolved and are now sharable. We call the “regular” connection as “personal connection”.

The problem with the “personal connections” is the difficult to make teamwork. The personal connections belong to you and different developers can’t use them. When a different developer needs to work with the same objects, they are required to create their own connection.

Using cloud connections, we can create a single, reusable connection to the data source and share it with all the developers in the team.

Read on to learn more about how they work now that the feature is a bit more mature.

Comments closed

Exploring Semantic Model Relationships with Sempy

Published 2024-10-09 by Kevin Feasel

Prathy Kamasani builds a graph:

Understanding the relationships between datasets is crucial in data analytics, especially in the world of self-service BI. Sempy, a Python library unique to Microsoft Fabric, allows users to visualise these relationships seamlessly. This post explores using Sempy to visualise semantic model relationships and view them in a Power BI Report. Viewing them in Notebook is easy and has been documented on MS Docs.

Click through for a notebook and explanation of the underlying code.

Comments closed

Referencing a Microsoft Fabric ML Model from another Workspace

Published 2024-10-08 by Kevin Feasel

Sandeep Pawar crosses workspaces:

I have written a couple of blogs about working with ML models in Microsoft Fabric. Creating experiments and logging and scoring models in Fabric is very easy, thanks to the built-in MLflow integration. However, the Fabric Data Science experience has one limitation. There are no model endpoints yet, and you cannot load a model from another workspace because the model URI, unlike in Databricks, does not reference a workspace. If you use MLFlowTransformer as shown in this blog, only the model from the workspace where the notebook is hosted is loaded. However, there is a workaround.

Read on for that workaround, as well as the core limitation associated with it.

Comments closed

Announcements from the European Fabric Community Conference

Published 2024-10-08 by Kevin Feasel

James Serra brings tidings:

A TON of new features announcements at the European Microsoft Fabric Community Conference help last week. The full list is here, and I wanted to list my favorite announcements from that list:

  • Access Databricks Unity Catalog tables from Fabric (public preview): You can now access Databricks Unity Catalog tables directly from Fabric. In Fabric, you can now create a new data item called “Mirrored Azure Databricks Catalog”. When creating this item, you simply provide your Azure Databricks workspace URL and select the catalog you want to make available in Fabric. Rather than making a copy of the data, Fabric creates a shortcut for every table in the selected catalog. It also keeps the Fabric data item in sync. So, if a table is added or removed from UC, the change is automatically reflected in Fabric. Once your Azure Databricks Catalog item is created, it behaves the same as any other item in Fabric. Seamlessly access tables through the SQL endpoint, utilize Spark with Fabric notebooks and take full advantage of Direct La

Read on for the rest of what James found exciting.

Comments closed

Spaces in Microsoft Fabric Delta Table Names

Published 2024-10-04 by Kevin Feasel

Sandeep Pawar is looking for a bit more space:

One of the annoying limitations of Direct Lake (rather of the SQL endpoint) was that you could not have spaces in table and column names in the delta table. It was supported in the delta table but the table was not query-able in the SQL endpoint which meant you had to rename all the tables and columns in the semantic model with business friendly names (e.g. rename customer_name to Customer Name). Tabular Editor and Semantic Link/Labs was helpful for that.

But at #FabConEurope, support for spaces in table names was announced and is supported in all Fabric engines. You have to use the backtick to include spaces, as show below.

Read on to learn more about how you can create these, what the limitations are, and then you can decide whether it’s worth it to have spaces in table names.

Comments closed

Recovering Power BI Reports You Cannot Download

Published 2024-10-03 by Kevin Feasel

Kurt Buhler grabs a report:

Below are some reasons why you might not be able to download your Power BI report or model from a workspace:

  • The report was created in the service:
    • Someone created the report manually (using the User Interface) and connects to a model in another workspace.
    • Someone created the report programmatically (for instance, using the REST APIs).
    • Power BI created the report automatically (for instance, it copied the report to a workspace that belongs to a later stage in a deployment pipeline)
  • You used the REST APIs to re-bind a report (changed which model it connects to as a data source).
  • The model has incremental refresh enabled.
  • The model uses automatic aggregations.
  • The model was modified via an XMLA endpoint.
  • Other scenarios described in the limitations in the Microsoft documentation.

When you encounter this scenario, you see something like the following image, which shows the Download this file option greyed out from the File menu of the Power BI report.

Read on to see how you can nonetheless recover these published reports using the semantic-link-labs library.

Comments closed