Microsoft Fabric: The Need To Do So And The Key Migration Factors

Microsoft Fabric: The Need To Do So And The Key Migration Factors

What is Fabric?

The Microsoft Fabric Platform offers a SaaS-ified, lake-centric, open, full-featured data, analytics, and AI platform that meets all of your data analytics requirements.

Microsoft Fabric revolutionizes data analytics and data engineering by endorsing the concept of storing only one copy of data in a central lake (one lake), using the industry-standard Delta Parquet format. Thus, businesses can avoid redundant data replication and have one single source of data.

This comprehensive, integrated approach allows businesses to set up streamlined and efficient data engineering processes. Now, you need not have to replicate data to work with different technologies. This prevents redundancies, streamlines data management, and ensures a true single source of data for decision-making and analysis.

Microsoft’s Fabric is a revolutionizing platform that redefines the data analytics landscape. It enables storage and utilization of data in a uniform format, preventing needless replication and allowing for a seamless integration with various Microsoft tools. Such technology enables organizations to work with a true single source of data, streamlining and restructuring their workflows and enhancing their data assets.

Why do I need to Change?

Despite Microsoft’s robust suite of analytical services for a complete platform, it comes with the following challenges:

  • Proprietary and open systems
  • Varied products and experiences
  • Mix of serverless and dedicated
  • Expertise and integration demands
  • Diverse business models
  • Steep learning curve

Fabric resolves such challenges; thereby offering a streamlined and unified analytics solution that spans the entire spectrum of data engineering, integration, real-time analytics, warehousing, and data science.

Fabric Design

The main identity of Fabric lies in its design. It flawlessly integrates Microsoft products – from data engineering and integration to real-time analytics/ data warehousing and data science, resulting in an integrated Power Business Intelligence (BI) experience. The comprehensive platform guarantees an effortless and smooth connection; thus, improving overall efficiency and collaboration.

Storage Layer:

  • OneLake acts as the storage layer of Fabric. It is auto-provisioned and all workloads/stages of Fabric are read and written to this single OneLake.
  • Auto-indexing of data in OneLake enables easy discovery, governance, sharing, and compliance.
  • All tabular data is stored in the industry-standard Delta Parquet format.

Compute Layers:

  • All compute engines such as Spark, Sql, KQL, and Analysis Services store their data automatically in OneLake.
  • All compute engines can directly access OneLake data without any additional imports.

Access Control

Control Plane: Users’ permissions are defined by 4 membership types: admin, contributor, member, and viewer.

Data Plane: A shared universal security model is imposed on top of OneLake, to ensure that data is accessible only to users with the right privileges. This security model is imposed across all computing engines.

Advantages of Using Fabric

Let us understand the benefits that Fabric brings:

Embraces Collaboration

In today’s data-driven landscape, collaboration is essential to gain insights. Departments need to share data seamlessly; which otherwise hinders effective collaboration.

Enables Data Integrity

Information is frequently stored in disparate databases, which results in discrepancies across departments. As data grows, its accuracy weakens and its usefulness decreases. OneLake enables centralizing data to resolve these issues.

Enterprise-wide Data Discovery

Fabric allows for the sharing of data between departments, which helps in identifying new opportunities and enterprise-wide inefficiencies.

Standardizes Formats and Tools

Fabric ensures that all teams/departments across the enterprise leverage the same data format and analytics tools.

Efficient Resource Utilization

Fabric prevents copying of the same dataset or downloading it for analysis via Excel, thus minimizing unnecessary resource usage.

Decentralized Data Teams

Traditional data architectures revolve around data lakes or data warehouses, acting as a central repository for all organizational data. A dedicated data team is responsible for handling this centralized structure and fulfilling data requests from different business teams.

  • Modern organizations are now adapting to operating with different domains, each concentrating on specific areas of growth. These domains depend on the central data team to be able to access the required data, which lacks scalability and significantly increases the time-to-insight.
  • In Microsoft Fabric, each business team can have a dedicated workspace storing data as well as the business logic. Each one of these workspaces can be allocated to one domain. Every domain has admins and contributors, among whom we can find a data owner and multiple data engineers.

Democratize Reports Creation

Users can create and deliver actionable insights by leveraging their preferred applications.

Federated Governance

As an organization grows, it becomes extremely difficult for central IT teams to handle the security of data at a granular level. Using Fabric, the central IT team sets automated frameworks and guidelines while the business manages aspects such as data privacy and quality in their areas.

Should your Organization Move to Fabric?

To choose Fabric or not is a decision that depends on your organization’s priorities. But looking at Fabric’s current feature set, the following is what we observe. Is expected to change as Fabric evolves.

Greenfield Projects:

Great to start with Fabric. The only factor to check is the cost aspect.

Existing Analytics Projects:

If you think that your organization will benefit from migrating to Fabric, then you must do so, or else stick to the current platform.

Things to Know Before Migrating

If your organization is looking to migrate then make note of the following points:

  • There are no automated upgrade paths available for existing Synapse workloads to Fabric, but migration guides are available. Depending on the workload, you will require different levels of adaptations to run them on Fabric.
  • Automatic upgrade of prevailing ADF pipelines is a feature request in progress, as per the feature status.
  • Mapping data flows is not available Fabric; however, Dataflows Gen2 is the new variant available in Fabric.
  • Openrowset() is not supported in Fabric. With the Shortcuts available in Fabric; you can create virtual copies of existing data lakes in locations such as Amazon, ADLS, or Google. These copies be used instead of openrowset(). However, this would require altering existing queries.
  • Dedicated SQL server pools are not available and only Serverless SQL Endpoints are accessible.
  • Capacity allocation to workloads is not available yet and, in a situation, where PowerBI users consume all the capacity, data pipelines will be affected.
  • Auto pause of Fabric capacity is not available yet but can be done manually for now.
  • GitHub is not yet supported; however, Azure DevOps repos are available.


This article is a comprehensive guide to Microsoft Fabric, providing insights into its advantages, design, and key considerations for migration. We aim to empower decision-makers with the knowledge required to navigate the transformative landscape of Microsoft Fabric. Aretove’s team of experienced professionals is well-versed in Microsoft Fabric’s features and capabilities ensuring that businesses can leverage the platform to its fullest potential. From data integration to advanced analytics, Aretove offers the technical expertise required to leverage the features of Microsoft Fabric.



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