
Dataflows Gen2 vs Data Factory Pipelines in Microsoft Fabric: What’s the Difference?
Dataflows Gen2 vs Data Factory in Microsoft Fabric: What’s the Difference? I have been asked this question several times in recent training sessions on Microsoft Fabric, so I jotted some notes down here.
Microsoft Fabric brings together the best of Microsoft’s data engineering, data integration, analytics, and AI capabilities into a single unified platform. For many teams adopting Fabric, one of the first questions that arises is:
“What’s the difference between Dataflows Gen2 and Data Factory Pipelines?”
Both can move, transform, and prepare data. Both live inside the Fabric experience. And both can be scheduled, monitored, and orchestrated. However, they serve different purposes, offer different strengths, and work best in different parts of the modern data lifecycle.
This post explains the key differences and provides practical examples to help you choose the right tool for your scenario.
What Are Dataflows Gen2?
Dataflows Gen2 are Fabric’s low-code data preparation and transformation solution. They are built on Power Query, the same engine used in Power BI and Excel, giving analysts and citizen developers a familiar, friendly interface.
Key Characteristics
- Low-code / no-code: Drag-and-drop transformation steps rather than writing SQL or Python.
- Power Query based: Ideal for data wrangling, cleansing, merging, shaping, and enrichment.
- Works well for mid-volume data: Excellent for business data preparation and M-code transformations.
- Outputs straight into Fabric: Can load data into Lakehouses, Warehouses, and KQL databases.
- Accessible to analysts: You don’t need a data engineering background to use it effectively.
When to Use Dataflows Gen2
Dataflows Gen2 shine in scenarios such as:
- Self-service data preparation for analysts building semantic models.
- Ingesting business application data (Excel files, SharePoint lists, Dataverse, SQL).
- Quick transformations such as splitting columns, merging tables, cleaning text, or deduplication.
- Prototyping datasets before handing them over to engineering teams.
If you know Power Query, you’ll feel at home immediately.
What Is Data Factory (in Fabric)?
Fabric’s version of Data Factory combines two things:
- Pipelines – orchestration and data movement.
- Dataflows (Power Query) and Notebooks (Spark) – heavy-duty transformation for engineers.
It is Microsoft’s full data integration and ETL/ELT platform, now tightly integrated into Fabric.
Key Characteristics
- Enterprise-grade orchestration with pipelines, triggers, and dependency management.
- Powerful connectors for large-scale ingestion, especially from cloud and on-premises systems.
- Supports Spark notebooks and data engineering workloads.
- Handles high-volume, complex pipelines.
- CI/CD friendly and suited for production data engineering.
When to Use Data Factory
Data Factory is designed for more complex engineering tasks, such as:
- High-volume ingestion from operational systems, APIs, or files landing in cloud storage.
- ETL/ELT using Spark notebooks, SQL scripts, and pipeline activities.
- Orchestrating multi-step workflows, including branching, loops, and conditional logic.
- Copying terabyte-scale datasets from Azure SQL Database, Synapse, ADLS, AWS S3, Oracle, and more.
- Building production-ready pipelines with monitoring, retries, and error handling.
If you are familiar with Azure Data Factory, this will feel like its next evolution within Fabric.
Dataflows Gen2 vs Data Factory: How to Choose?
Here is a simple way to think about it:
Choose Dataflows Gen2 when:
- You want low-code data shaping.
- Business analysts are preparing their own datasets.
- You need simple ingestion or transformation.
- The data volumes are small to medium.
- The source systems are Excel, SharePoint, Dataverse, or SQL.
Choose Data Factory when:
- You are building enterprise pipelines.
- You need orchestration, scheduling, and dependencies.
- You are working with large or complex datasets.
- You require Spark, notebooks, Data Engineering, or SQL pipeline logic.
- Data movement needs to be integrated into CI/CD or operated at production scale.
A Combined Approach
In many organisations the best approach is both, working together:
- Data Factory pipelines handle ingestion from source systems into the Bronze layer.
- Dataflows Gen2 then apply transformations to shape and enrich the data for the Silver layer or the semantic model.
This layered approach provides scalability, governance, and flexibility while still enabling self-service analytics.
Need help applying this in practice?
If your organisation is using Power BI or Microsoft Fabric and needs clarity around architecture, governance, or next steps,
The Data Platform Accelerator is designed to help.
It’s a focused engagement that assesses your current setup and delivers a practical roadmap you can execute.
👉
Learn more about The Data Platform Accelerator
Summary
While Dataflows Gen2 and Data Factory sit side-by-side in Microsoft Fabric, they target very different users and workloads:
- Dataflows Gen2 → Best for analysts, low-code transformations, quick data preparation.
- Data Factory → Best for engineers, enterprise data pipelines, complex ingestion, and orchestration.
Understanding these differences ensures your team uses the right tool for the right job, helping you build efficient, scalable, and well-governed data solutions in Microsoft Fabric.
If you’re teaching or adopting Fabric, this distinction is one of the most important concepts to get right early.
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Power BI & Microsoft Fabric Consulting and Training | 2025 Review
Power BI & Microsoft Fabric Consulting and Training | 2025 Review
As the final working day of 2025 draws to a close here at GRE Towers, it feels like the right time to reflect on what has been another highly successful year for data consulting, Power BI delivery, Microsoft Fabric projects, and technical training.
Throughout 2025, we’ve worked with organisations across the public sector, private sector, fintech, insurance, retail, and not-for-profit space, helping them make better decisions using data.
Data consulting highlights from 2025
Over the past year, our data consulting and advisory services have included:
- Embedding Power BI dashboards directly into a fuel delivery company’s application
- Providing a Virtual DBA service to a large software licensing company, managing and optimising their SQL Server estate
- Delivering ongoing Virtual DBA services for a fast-moving retail organisation
- Designing and architecting a Microsoft Fabric deployment for a local authority
- Providing fractional CEO and CTO services to a healthcare startup (more on this in 2026)
- Delivering fractional CIO / CTO support to NICS Wellbeing
- Supporting a large insurer with data strategy, business alignment, and BI modernisation, including a roadmap to migrate legacy BI infrastructure to Microsoft Fabric
- Optimising Power BI and Microsoft Fabric capacity for an insurer, delivering significant cost savings on their F512 capacity
- Implementing a data engineering solution for risk reporting with a fintech operating in the insurance broker space
These projects reflect a growing demand for modern analytics platforms, cost-effective Fabric capacity planning, and strategic data leadership.
Power BI, Microsoft Fabric, and SQL training delivered in 2025
Training remains a core part of what we do, and in 2025 we delivered a wide range of bespoke and commercial training programmes, including:
- Bespoke Power BI training for a leading food manufacturer
- Bespoke Power BI and Paginated Reports training for two leading UK police forces
- Bespoke Microsoft Fabric training for a large local authority
- SQL training for a large local authority
- Authoring a commercial PostgreSQL DBA training course for a major training provider
- Delivering multiple Microsoft-certified courses for large Microsoft training partners
Our training focuses on real-world use cases, ensuring teams can apply what they learn immediately.
Data consulting and training plans for 2026
Looking ahead, 2026 is already shaping up to be another strong year.
Consulting in 2026
- Continuing data engineering and risk reporting work with a fintech in the insurance broker space
- Ongoing Virtual DBA services for a large software licensing company
- Continued SQL Server and platform support for fast-moving retail
- Supporting a not-for-profit organisation with Power BI development, focusing on KPI reporting and insight delivery
Training in 2026
You can view our public training schedule on the website, with new dates added regularly.
Looking for Power BI, Microsoft Fabric, or data consulting support in 2026?
If you’re planning to improve your data analytics, reporting, or platform strategy in 2026, now is the ideal time to start the conversation.
Whether you need:
- Power BI development or optimisation
- Microsoft Fabric architecture and cost optimisation
- SQL Server or PostgreSQL DBA support
- Fractional CIO / CTO or data leadership
- Tailored training for your team
We can help.
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2026 Microsoft Data & Analytics Training Schedule
Our 2026 Microsoft Data & Analytics Training Schedule Is Live
We’re excited to share our public training schedule for 2026, covering three of the most in-demand Microsoft data certifications:
- PL-300 – Power BI Data Analyst (3 days) – £995 per seat
- DP-600 – Implementing Analytics Solutions Using Microsoft Fabric (4 days) – £1,200 per seat
- DP-700 – Implementing Data Engineering Solutions Using Microsoft Fabric (4 days) – £1,200 per seat
Across 2026, we will run 24 instructor-led courses, split evenly between UK time and North American time. UK and US courses do not overlap and do not run in the same week, and we’ve planned around key UK bank holidays and US federal holidays.
2026 Course Schedule (UK & North America)
All dates below are scheduled in separate weeks for UK vs North America delivery each month.
| Month | UK (UK time) | North America (NA time) |
|---|---|---|
| January | PL-300 — Mon 12 Jan to Wed 14 Jan 2026 | DP-700 — Mon 26 Jan to Thu 29 Jan 2026 |
| February | DP-600 — Tue 10 Feb to Thu 12 Feb 2026 | PL-300 — Tue 17 Feb to Thu 19 Feb 2026 |
| March | PL-300 — Tue 10 Mar to Thu 12 Mar 2026 | DP-700 — Tue 24 Mar to Fri 27 Mar 2026 |
| April | DP-700 — Tue 7 Apr to Fri 10 Apr 2026 | PL-300 — Mon 20 Apr to Wed 22 Apr 2026 |
| May | PL-300 — Tue 12 May to Thu 14 May 2026 | DP-600 — Tue 26 May to Fri 29 May 2026 |
| June | DP-700 — Tue 9 Jun to Fri 12 Jun 2026 | PL-300 — Tue 16 Jun to Thu 18 Jun 2026 |
| July | PL-300 — Mon 6 Jul to Wed 8 Jul 2026 | DP-700 — Tue 14 Jul to Fri 17 Jul 2026 |
| August | DP-600 — Tue 18 Aug to Fri 21 Aug 2026 | PL-300 — Tue 25 Aug to Thu 27 Aug 2026 |
| September | PL-300 — Mon 7 Sep to Wed 9 Sep 2026 | DP-600 — Tue 15 Sep to Fri 18 Sep 2026 |
| October | DP-700 — Tue 6 Oct to Fri 9 Oct 2026 | PL-300 — Tue 20 Oct to Thu 22 Oct 2026 |
| November | PL-300 — Tue 10 Nov to Thu 12 Nov 2026 | DP-700 — Mon 30 Nov to Thu 3 Dec 2026 |
| December | DP-600 — Tue 8 Dec to Fri 11 Dec 2026 | PL-300 — Tue 15 Dec to Thu 17 Dec 2026 |
Who These Courses Are For
Our public courses are particularly well suited to:
- Data analysts and BI professionals
- Data engineers and analytics engineers
- Consultants and contractors
- Teams transitioning to Microsoft Fabric
- Organisations standardising on Power BI and the Microsoft data platform
We aim for an average of 10 attendees per session, keeping class sizes small enough for meaningful interaction, questions, and discussion.
Reserve Your Seat
If you would like to reserve a seat, discuss group bookings, or explore private or tailored delivery, please get in touch.
👉 If you would like to reserve a seat, please get in touch and contact us.
Early expressions of interest help us confirm capacity and ensure you get the dates that work best for you and your team. If your prefer team training contact me directly and we can disucss what you need
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