How to Build Data Pipelines in Microsoft Fabric Step by Step
You might feel stressed when you start Building Data Pipelines in Microsoft Fabric. Many people have problems like linking different data sources. It can be hard to keep data quality high. Handling errors in workflows is also tricky. Some people find it tough to make pipelines bigger as data grows. Managing costs for big projects can be hard too. Others have trouble with security or following rules. Learning new tools can also be a struggle. This guide gives clear steps for each stage. Before you start, check if you have the right access and tools.
Key Takeaways
First, make sure you have the correct Microsoft 365 account and permissions. This helps you avoid problems when setting up. - Make a workspace and lakehouse to keep your data safe and organized. Use the medallion architecture for this. - You can use templates or make pipelines yourself. These help you move, change, and manage data from different places. - Add activities like Copy Data and Dataflow Gen2. These help you clean and get your data ready in a good way. - Run, watch, and plan your pipelines to keep data up to date. Use built-in tools to find and fix problems early.
Prerequisites
Account and Access
You need the right account before you start. Your account must have a Microsoft 365 or Office 365 license. For example, Microsoft 365 Business Basic or Office 365 E1 work. These licenses let you use Microsoft Teams. Teams is needed if you want to send pipeline notifications. If you use a service account for tasks, it needs the right license too. Ask your IT administrator if you are not sure about your license. The right account helps you avoid setup problems.
💡 Tip: Always use your company’s official account. Personal accounts might not have the right permissions.
Permissions and Tools
You need special permissions and tools to set up data pipelines. Here is a checklist to help you start:
1. Give roles like Fabric Administrator or workspace roles to control access. 2. Use gateway and connection roles for safe data connections. 3. Set up data gateways to connect to your data sources. 4. Configure environments to manage compute and runtime settings. 5. Use deployment pipelines for content promotion and version control. 6. Manage sharing permissions at different levels to keep data safe. 7. Assign admin or viewer roles so your team can work together. 8. Track deployment history and compare content to improve teamwork.
The right permissions and tools help you build and manage data pipelines easily.
Workspace and Lakehouse
Create Workspace
You must make a workspace before building data pipelines in Microsoft Fabric. A workspace is like a main folder for your projects. It helps keep your work neat and safe. Workspaces let you split up development and testing. This stops mistakes from hurting your main data. Teams can use workspaces to work together better. You can control who can see or change things in a workspace.
You can give each team member a special role.
Workspaces help you move through Development, Test, and Production.
Only workspaces with the right settings can use deployment pipelines.
Each workspace holds your pipelines, so it is easier to manage them.
To make a workspace, do these steps:
Open the menu on the left and pick "Workspaces."
Click "+ New Workspace."
Type a name for your workspace.
To find your workspace later, go to "Workspaces" and pick its name.
📝 Note: Give your workspace the right settings and permissions. This helps you control your pipeline and keeps your data safe.
Set Up Lakehouse
After making a workspace, you need to set up a lakehouse. A lakehouse is one place to keep all your data. It works with many types of data and keeps things tidy. Lakehouses use OneLake, so you can grow your storage easily. You can handle both batch and real-time data. The lakehouse uses medallion architecture to help make your data better.
You can look at raw and clean data right away, saving time.
Shortcuts and Mirroring help keep your data new and stop copies.
You can use Power BI and Spark to study and show your data.
Security tools like RBAC and Microsoft Purview help you follow rules and keep data safe.
To set up a lakehouse, do these steps:
Open your workspace.
Click "New item" and pick "Lakehouse."
Name your lakehouse.
Download some sample data, like a CSV file.
Make a Dataflow Gen2 and add your data file.
Change table names to follow the rules.
Link the dataflow to your lakehouse as the place to send data.
Publish and refresh the dataflow to load your data.
Look at your data in the lakehouse.
Add tables to the semantic model and sync with Power BI to make reports.
💡 Tip: Use the medallion architecture (Bronze, Silver, Gold) to sort your data and make it better at each step.
Building Data Pipelines
Building Data Pipelines in Microsoft Fabric helps you move and change your data. You can use templates or start with a blank pipeline. Templates are ready-made plans for common data jobs. They help you get started fast. If you want more control, you can build your own pipeline step by step. Both ways let you bring in, move, and change data easily.
💡 Tip: Templates help you work faster and make fewer mistakes. You can copy sample datasets to your Lakehouse in just a few minutes. This makes it easier to start and build your pipeline.
New Pipeline
To start, you need to make a new pipeline. Go to your workspace and click "New pipeline." You can pick a template or start with a blank one. Templates have built-in steps for jobs like copying or changing data. They save you time because you do not have to build everything yourself. If you want to choose every step, use a blank pipeline and add what you need.
Pipelines in Microsoft Fabric have different parts. Each part does something important. The table below shows the main parts and what they do:
When you build Data Pipelines, you use these parts to watch and manage your data. You can also use tools to set up times for your pipelines to run by themselves.
Data Sources
You can connect to many types of data sources in Data Pipelines. Microsoft Fabric works with cloud and on-premises sources. You can use Azure storage, Azure SQL Server, and other cloud services. If your data is on-premises, you can use the Data Gateway to connect safely.
Some connectors you can use are:
Azure Blob Storage
Azure Data Lake Storage Gen2
SQL Server
Oracle
MySQL
PostgreSQL
Salesforce
SAP
You can also connect to other sources and file types. Microsoft Fabric lets you manage connections and gateways in the settings. You can use different ways to sign in, like Basic, OAuth2, or Service Principal. This helps you bring in data from almost anywhere.
📝 Note: Always check your connection settings and permissions before you start. This helps you stop errors when you bring in data.
Destinations
After you bring in data, you need to pick where it goes. The most common places in Data Pipelines are the Lakehouse, Fabric Data Warehouse, and OneLake storage. These places let you store, change, and study your data.
For example, you can use Copy Data to move data from outside into OneLake storage. This storage helps your Lakehouse, so you can manage files and tables. You can also send data to the Fabric Data Warehouse for deeper study.
You can use the medallion architecture to sort your data in layers. The Bronze layer has raw data. The Silver layer has cleaned and changed data. The Gold layer has data ready for reports and study. This setup makes your data better and easier to trust.
🚀 Advanced Tip: Try metadata-driven pipelines for big projects. These pipelines use tables to manage sources, destinations, and load types. You can use the same pipeline for many sources by changing the metadata. This saves time and makes your pipelines easier to take care of.
Building Data Pipelines in Microsoft Fabric gives you tools to bring in, change, and store data. You can use templates, connect to many sources, and send data to safe places. The medallion architecture and metadata-driven pipelines help you grow and manage your data with ease.
Add Activities
When you make a data pipeline in Microsoft Fabric, you add activities to tell the data what to do. Each activity has its own job. You can use different activities together. This helps you build a strong pipeline that can do many things.
Copy Data
The Copy Data activity lets you move data from one place to another. You can use it to get data from over 100 sources. You can send the data to places like OneLake or Fabric Warehouse. This activity is the main way to move data in Building Data Pipelines. You can use the Copy Assistant to help you, or you can set up everything by yourself in the pipeline canvas.
💡 Tip: Use the Copy Data activity when you have a lot of data to move or want to copy data without writing much code.
Here are some good ways to use Copy Data:
Make or choose connections for your source and where you want the data to go.
Match your source data to the destination schema. You can let the system find it or set it yourself.
Change settings for speed, like how fast it goes or how many things it does at once.
Turn on fault tolerance so bad rows or files get skipped.
Use logging to see what was copied or skipped.
Use parameters to make your pipeline work for more than one job.
Transform Data
You can change and clean your data with transformation activities. Microsoft Fabric gives you many ways to do this. Dataflow Gen2 lets you use over 300 data and AI-based changes with an easy interface. You can also use notebooks, SQL scripts, or stored procedures for harder changes.
You can add these activities to your pipeline to clean, join, or get your data ready before you load it to its final place.
Parameterization
Parameterization makes your pipelines flexible. You can give values to your pipeline instead of putting them in the code. This means you can use the same pipeline for different data sources or places. You save time and make fewer mistakes.
Use parameters to set connections, file names, or table names.
Give values when the pipeline runs to change what it does.
Use parameters with expressions for even more control.
📝 Note: Parameterization helps you move your pipeline from development to test or production without changing the setup each time.
Run and Monitor
Execute Pipeline
After you set up your pipeline, you can run it. Go to your workspace and find the pipeline you made. Click on it and choose "Run." You can run the whole pipeline or just one activity. If you use parameters, type in the values before you start. This step lets you test your pipeline before using it for real work. You can use deployment rules to move your pipeline from test to production. These rules help keep your work safe and neat.
💡 Tip: Always test your pipeline in a test area first. This helps you find mistakes before you use it for real.
Monitor Runs
When your pipeline runs, you should check if it works right. Microsoft Fabric gives you ways to watch your pipeline runs:
Go to your workspace and pick your pipeline.
Click "View run history" to see what happened before.
Use the monitoring hub to find certain runs.
Look at things like run status, errors, inputs, outputs, and speed.
Export the data to a CSV file if you want to study it more.
Use the Gantt chart to see how long each run takes.
If something fails, you can run the whole pipeline again or just the part that failed. You can also make alerts by setting up another pipeline. This pipeline can send emails if something goes wrong. Your team will know about problems right away.
Logs and Validation
Logs and validation help keep your pipeline working well. Microsoft Fabric uses control tables and auditing to watch for errors and speed. You can add steps to check your data, like looking for missing or repeated values. If the pipeline finds bad records, it marks them but does not stop everything. Logs keep track of these problems so you can fix them later and run the pipeline again.
You can use tools like Great Expectations to check your data. These tools make reports that show if your data is good. Error logs can go to Azure Monitor, which helps you set up alerts and watch for problems. This helps you keep your data clean and your pipeline running well.
📝 Note: Good logs and validation help you find problems early. This keeps your data safe and trusted when Building Data Pipelines.
Schedule Pipeline
Set Frequency
You can make your data pipeline run on a schedule. Microsoft Fabric lets you pick how often it runs. You can choose every minute, hour, day, or week. These options help you fit the pipeline to your needs.
To set this up, open your pipeline and go to the schedule settings. Turn on the schedule. Pick how often you want it to run. You can also set the time zone, start date, and end date. If you want to change the schedule later, you can edit or delete it in the workspace menu.
📝 Tip: You can use a parameter for how often it runs. This lets you change the timing without changing the whole setup.
If you need more choices, you can make more triggers. For example, you might run your pipeline every hour during busy times. You could run it once a day when things are slower. Microsoft Fabric does not let you use cron expressions or many schedules for one pipeline yet. But you can make extra pipelines or use special logic as a workaround.
Automate Runs
Automating your pipeline saves time and keeps your data new. When you set a schedule, Microsoft Fabric runs it for you. You do not have to start it by hand. Automation helps you avoid mistakes and keeps your data up to date.
Here are some good things about automating your pipeline:
You can set up tasks like copying data or running scripts.
Automation works for both batch and real-time jobs.
Built-in tools help you watch each run.
You can link your pipeline to other Fabric services like Lakehouses or Power BI.
Pipelines can run on a schedule, by event, or when you start them yourself.
If you want your pipeline to run when something happens, you can use Power Automate or Logic Apps. These tools can start your pipeline when a new file comes in or when someone presses a button in an app. This gives you more ways to control when your data moves.
🚀 Did you know? Automating pipelines helps your team work faster and makes your data better. You can spend more time learning from your data instead of doing things by hand.
Enhance and Modify
Add Activities
You can make your data pipeline better by adding new activities. Microsoft Fabric lets you use many kinds of activities to help your pipeline. Here are some things you can do:
Turn on incremental refresh in your semantic models. This lets your pipeline only update new or changed data. It saves time and uses less power.
Use composite models to link your Fabric semantic models with other data models. This gives you more ways to use data from different places.
Set up automatic aggregations. Machine learning can help your pipeline answer questions faster by making smart summaries.
Manage hybrid tables that use both import and DirectQuery partitions. This helps you refresh data and control partitions better.
Use autobinding to connect reports and models in each pipeline stage. This makes it easier to handle changes.
Organize your workspace with folders. This keeps your items neat and easy to find.
Update Power BI apps for each stage. This lets users try new features before they are live.
Move content between pipeline stages. You can move workspaces or update content when you need to.
💡 Tip: Adding activities helps your pipeline stay ready for new needs.
Update Logic
You can also make your pipeline work better by changing its logic. Try logical partitioning to split your data into smaller parts. This helps your pipeline run faster. Use activities like 'For Each' to work on many data partitions at the same time. Set a high batch count so your pipeline can do up to 50 tasks at once. Turn off sequential execution to make it go even faster. If you use 'Invoke Pipeline', the parent pipeline can keep running while child pipelines finish. These changes can make your load times much shorter.
Always check the limits of your source and destination systems. Too much parallel work can cause errors or slow things down. You may need to watch your pipeline and fix problems as they happen.
📝 Note: Using version control, like linking your workspace to a Git repository, helps you track changes and go back if something goes wrong. This is a smart way to build Data Pipelines in Microsoft Fabric.
You now know the main steps to build Data Pipelines in Microsoft Fabric. The lakehouse can be your main place for data. You can set up workflows to run by themselves. Built-in tools help you watch your results. Try using notebooks to change your data. Use Power BI to make reports. As you get better, try out advanced features. You can refresh the semantic model, use Copilot for pipelines, and work with REST APIs to automate tasks.
🚀 Keep trying new things and find better ways to use your data.
FAQ
How do you fix a failed pipeline run in Microsoft Fabric?
Look at the run history to see what went wrong. Check the logs to find out the problem. You can try running just the failed part again. Or you can run the whole pipeline again. Make sure your connections and permissions are correct. Fix any wrong settings before you try again.
Can you use your own data sources with Microsoft Fabric pipelines?
Yes, you can connect to lots of data sources. Use the built-in connectors for cloud or on-premises data. Set up a gateway so your data is safe. Always test your connection before you run the pipeline.
What is the medallion architecture in a data pipeline?
The medallion architecture puts your data into three layers. Bronze is for raw data. Silver is for cleaned data. Gold is for data ready for reports. This helps you manage and improve your data step by step.
How do you schedule a pipeline to run automatically?
Open your pipeline and go to the schedule settings. Choose how often you want it to run. Pick the time zone and start time. Save your changes. Microsoft Fabric will run your pipeline on the schedule you picked.
Can you monitor pipeline runs in real time?
Yes, you can watch your pipeline runs in the monitoring hub. You can see if it is running, if there are errors, and how fast it goes. Set up alerts to get a message if something goes wrong. This helps you fix problems fast.