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Loading Data Into OneLake via ADLS Gen2 SFTP
Microsoft Fabric

Loading Data Into OneLake via ADLS Gen2 SFTP

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.
Designing Microsoft Fabric Workspaces
Microsoft Fabric

Designing Microsoft Fabric Workspaces

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.
Delta Lake logo, heart icon, Apache Hudi and Iceberg icons
Delta Lake

How Can Delta Lake 3.0 Help You?

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.
Microsoft Fabric vs. Azure Synapse Analytics
Data

Microsoft Fabric vs. Azure Synapse Analytics

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.
5 Mistakes When Building Data Warehouses
Data

5 Mistakes When Building Data Warehouses

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.
First Impressions of Microsoft Fabric
Data

First Impressions of Microsoft Fabric

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.
From Warehouses to Lakehouses: The Journey
Data

From Warehouses to Lakehouses: The Journey

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.
What is a Lakehouse?
Data

What is a Lakehouse?

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.

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