If you’re diving into Microsoft Fabric, you’ve likely heard about its powerful capabilities for unified analytics. One of its standout features? Notebooks. Whether you’re coming from a data science, engineering, or BI background, notebooks provide a flexible space to explore, transform, and visualize data — all within the Fabric ecosystem.

In this guide, we’ll walk through how to get started with Notebooks in Microsoft Fabric — from creating your first notebook to running code and visualizing results. No fluff, just a practical walkthrough to help you hit the ground running.

This post is second in series that helps Partners and Customers plan Fabric Configuration for new and existing deployments. You can find the first post in this series here : 

https://community.fabric.microsoft.com/t5/Fabric-platform-Community-Blog/Microsoft-Fabric-CAF-Config...

As organizations move toward unified analytics platforms, Microsoft Fabric offers two powerful data storage models: Lakehouses and Data Warehouses. Each has unique advantages, and understanding when and how to use them is essential for effective data engineering and analytics.

This article explains the difference between Lakehouses and Warehouses in Fabric, shows how to create simple tables and load data, and includes links to practical exercises to get started.

Lakehouse vs. Data Warehouse in Microsoft Fabric
🔹 What Is a Lakehouse?
A Lakehouse combines the scalability of a data lake with the structure of a data warehouse. It stores structured, semi-structured, and unstructured data in open formats such as Parquet and Delta.

Key Features:

Supports files and tables in the same environment.
Ideal for big data analytics, data science, and machine learning.
Works seamlessly with Notebooks, Spark, and PySpark.

What Is a Data Warehouse?
A Data Warehouse in Fabric is optimized for structured data and BI reporting. It follows traditional SQL-based modeling and is best suited for OLAP workloads, business dashboards, and high-performance queries.

Creating Tables and Uploading Data
Let’s walk through how to create tables in both Lakehouses and Warehouses inside Microsoft Fabric.

🔹 In a Lakehouse:
Open your Lakehouse from the Fabric workspace.
Upload a CSV or Excel file.
Use the Data Engineering interface or a Notebook to create a Delta table

df = spark.read.csv("/Files/sales.csv", header=True, inferSchema=True)
df.write.format("delta").saveAsTable("SalesData")

In a Warehouse:
Go to your Warehouse in Fabric.
Use the SQL Editor to create a table:

CREATE TABLE Products (
ProductID INT PRIMARY KEY,
Name NVARCHAR(100),
Price DECIMAL(10,2)
);

3. Insert data manually or use the Load Data tool to import from OneLake, Excel, or an external source.

Practice Labs and Learning Resources
Here are some official and community resources where you can practice working with Lakehouses and Warehouses:

🔗Implement a Lakehouse with Microsoft Fabric - Training | Microsoft Learn
🔗Implement a data warehouse with Microsoft Fabric DP-602T00 - Training | Microsoft Learn
🔗 Sign in to your account

Choosing between a Lakehouse and a Warehouse depends on your workload. For data science and big data exploration, Lakehouse is ideal. For business intelligence and structured data analytics, the Data Warehouse provides better performance and SQL capabilities.

let’s connect on LinkedIn: https://www.linkedin.com/in/rufyda-abdelhadirahma/

Thinking of taking the DP-700 exam? Here’s how I passed it—and why it could change your career in data engineering with Microsoft Fabric.

Written in a friendly, simple style — for real beginners.

Overview

Over the past year, I’ve had the incredible opportunity to help Microsoft customers unlock the potential of Microsoft Fabric Capacities (FSKUs) by transitioning from Power BI Premium Capacities (PSKUs) or as they embark on their Fabric journey. During these engagements, we’ve tackled not just technical features, architecture design, deployment patterns, capacity planning, but also business considerations such as reservation purchasing strategies and scoping options to demystify how reservations work. Common questions I’ve frequently encountered are how to confidently navigate the reservation purchasing process, understand the scoping flexibility, and calculate consumption units effectively to maximize both value and efficiency.  

My hope is that this article will make your voyage smoother, offer clarity on these decisions, and empower you to make the most of your reservations when stepping into the world of Microsoft Fabric capacity planning!

🔧

Logic App Solution to Pause Fabric Capacity:

"Take control of your Microsoft Fabric costs with a smart, automated Logic App that pauses unused capacity—seamlessly, securely, and on your schedule. Whether it's nights, weekends, or idle hours, this solution ensures you're only paying for what you use—no more, no less."

𝗖𝗮𝗹𝗹𝗶𝗻𝗴 𝗮𝗹𝗹 𝗱𝗮𝘁𝗮 𝗲𝗻𝘁𝗵𝘂𝘀𝗶𝗮𝘀𝘁𝘀!

Are you ready to level up your impact in the Microsoft Fabric Community? The new Fabric Super User landing page is where you can get all the details. Become the hero our community deserves!

Managing tenant settings in a Fabric environment can be a complex task, especially when it comes to tracking changes, updates, and new features that are sometimes enabled by defalut. To simplify this process, I’ve outlined two options to ensure you stay up to date on modified, new, and upcoming Fabric settings.