Blog

The much awaited Synapse Link Dataverse capability for Fabric is here. You can now create a managed Lakehouse within your Fabric tenant with a few clicks, and send your Dataverse data (including Microsoft Dynamics 365) directly into Fabric as delta tables.

In this design series, we're going to be using Microsoft Fabric to design a corporate-wide Lakehouse, and demonstrate its capabilities.

In this design series, we're going to be using Microsoft Fabric to design a corporate-wide Lakehouse, and demonstrate its capabilities.

In this design series, we're going to be using Microsoft Fabric to design a corporate-wide Lakehouse, and demonstrate its capabilities.

In this design series, we're going to be using Microsoft Fabric to design a corporate-wide Lakehouse, and demonstrate its capabilities.

ADLS Gen2 has a neat feature allowing you to expose an SFTP endpoint from your storage. Any files uploaded land on the storage account directly. This feature isn’t available in OneLake, but that doesn’t mean you can’t combine ADLS Gen2 and OneLake to achieve SFTP ingestion.

Azure Durable Functions are convenient when you need to do long-running custom operations. Now, like Synapse and Azure Data Factory, we can call Durable Functions from Fabric pipelines. Let’s dive into how.

Fabric currently lacks the capability to call Synapse pipelines, which prevents Fabric from joining forces with your existing Synapse investment. However, Synapse pipelines can be triggered via the REST API, and with the recent Service Principal support in Fabric, we can do that with AAD auth.

Dataverse is the superpower that backs Power Platform and Microsoft Dynamics 365, allowing you to keep your data in table format without the fuss of database management. Let's connect it to your Fabric instance and make the data available for Power BI Direct Lake support.

Let's use Medallion Architecture in Microsoft Fabric and build a Lakehouse using Pipelines and Dataflows. We'll also discuss the responsibilities and the structure of the Bronze, Silver and Gold layers of the OneLake.

You can now use Azure AD (Microsoft Entra ID) Service Principals in Fabric Dataflows when connecting to various Azure and web resources, including Synapse Analytics, ADLS Gen2, Azure Blob Storage and Microsoft Dataverse.

Although there are many good resources online explaining how to start using Microsoft Fabric, there is a lack of guidance on adopting Fabric if you already invested in Synapse Analytics. Nothing prevents you from using Synapse Analytics and Fabric together.

Microsoft Fabric might be an upgrade to the Power BI game, but how do you move forward when you already have a massive investment in a data platform on your Azure cloud?

There are some Azure Container Apps features released to GA last week, and I wanted to recap those here and explain how they can be of use to you. Especially the Secret Mounts and the Key Vault Secret References are very important if you ask me.

Microsoft Fabric extends the Power BI workspaces with more item types, but those workspaces come with a lot of baggage. If you're coming from Azure Synapse Analytics or Data Factory, it may not be easy to figure out how to utilise workspaces best. We'll dive into it in this article.

Announced as part of Microsoft Fabric, OneLake is a tenant-wide managed data lake storage. More end-user friendly than ADLS Gen2, it gives a OneDrive-like experience to the users. Let's compare OneLake and ADLS Gen2's features.

Databricks announced the v3.0 of Delta Lake. Apart from the bells and whistles, it has one powerful feature: Support for Apache Hudi and Iceberg. When used in the right place, the support for Hudi and Iceberg can unlock many opportunities.

Fabric differs significantly from more traditional data platforms like Synapse Analytics and Databricks. It gives it ease of use, but it also takes away some features away. In this article, we’ll be talking about those differences, and when to use Fabric, when to avoid it.

Data warehouses would grow out of size, become underperforming, require scaling up and become costly. They would become a black hole in the company’s budget, and people spend more effort to keep it alive and breathing, rather than getting value out of that investment. Let’s go through some mistakes.

I finally got the time to provision myself a trial version of Microsoft Fabric to explore its capabilities and bend it to my will. It’s new and shiny, but it’s still in preview, so we’ll see how the end product will look like in a year. But I wanted to share my first impressions of it.

Historically, database technologies came with their data and compute capabilities coupled. If you wanted to use the query capabilities of a specific database, you had to copy/move the data into that database. This all changed with Data Lakes and Lakehouses.

Lakehouses are basically Data Warehouses built on top of Data Lakes using primarily Spark-based data processing technologies. They make the data processing, reporting, and analytics a breeze, but there’s nothing groundbreaking about them.