4 Typical Use Cases for Getting Data into Microsoft Fabric

December 15, 2025

This article explains the most common Microsoft Fabric ingestion use cases we see in large organizations and how to choose the right ingestion approach for each scenario. Ingestion is not just a technical choice. It’s a decision that influences performance, operational efficiency, and cost.

Microsoft Fabric offers a broad range of tools for data ingestion — from drag-and-drop interfaces to fully coded Spark notebooks. But how do you navigate all these options?

Ingesting data into Microsoft Fabric is not a one-dimensional technical task. The right Microsoft Fabric use case depends on the type of data, its location, required refresh frequency, and the skills of the user. In practice, we repeatedly see several recurring situations where tools such as Dataflows Gen2, Pipelines, or Eventstreams can be used effectively.

Microsoft Fabric Ingestion Use Cases

The four scenarios below cover the most common needs of large organizations we’ve encountered on projects – from regular ERP reporting to real-time infrastructure monitoring.

1. Reporting on Operational Systems (ERP, CRM, Databases)

You need regular (daily/hourly) reporting from source systems into Lakehouse or Warehouse storage, e.g., for operational reporting or further data processing.

• What it is: Automated transfer of tabular data from on-prem via a gateway.
• Typical Microsoft Fabric use case: Automated movement of structured data from cloud or on-prem (via data gateway) storage for operational reporting in Power BI or further analysis by Data Science.
• Recommended ingestion tools: Pipelines, Copy Activity, SQL.

2. Self-Service BI from Excel/CSV Files (OneDrive, Teams)

Your analysts need to load their data independently, without relying on IT.

• What it is: Loading and automatic refresh of M365 files.
• Typical Microsoft Fabric use case: A self-service BI approach where analysts load extracts stored on OneDrive or Teams directly into a Power BI semantic model, without any IT department involvement.
• Recommended ingestion tools: Dataflows Gen2, OneDrive / SharePoint.

 3. One-Off Analysis of Large Datasets (from Data Lake)

You need to process large amounts of data for models, planning, or reporting on a one-off basis.

• What it is: Processing of files (CSV, Parquet, Delta) using Spark.
• Typical Microsoft Fabric use case: Connecting existing data extracts in CSV/Parquet/Delta format for analysis of large (e.g., historical) datasets directly in the Lakehouse, without physically copying/moving them into Fabric platforms, with only minimal IT department support.
• Recommended ingestion tools: Shortcut.

4. Real-Time Monitoring (Sensor & IoT Data)

You need real-time data for operational decisions. You monitor operational incidents, application logs, or infrastructure statuses.

• What it is: Streaming logs/DATA into KQL for immediate analysis.
• Typical Microsoft Fabric use case: Continuous processing of sensor/IoT data or operational logs in near real-time and their subsequent reporting with minimal data latency.
• Recommended ingestion tools: Eventstreams / Spark Structured Streaming.

Ingestion Isn’t Just a Technical Step. It’s a Decision

Microsoft Fabric provides tools for a wide range of users — from IT engineers to business analysts. The key to using them effectively is selecting the right ingestion use case. Whether you are loading data from spreadsheet systems, file storage, or streaming events, one principle always applies: simplicity, performance, and automation always go hand in hand — if you choose the right method and tool.

There Is No “Best Tool,” Only the Most Suitable One

The question isn’t which tool is the best. What matters is who will upload the data, how often, and where. The decision on how to get the data into Microsoft Fabric is strategic. It can save you weeks of work or add weeks of unnecessary effort.

Author: Josef Pinkr specializes in data ingestion into Microsoft Fabric and works as a Senior Architect at Adastra.