Mirroring in Microsoft Fabric

February 9, 2025

10 Minutes

As the demand for AI-powered solutions continues to grow, businesses are seeking ways to leverage their own data and create custom models that address their specific needs.

Azure AI Studio: Empowering Businesses to Build Custom AI Models

As the demand for AI-powered solutions continues to grow, businesses are seeking ways to leverage their own data and create custom models that address their specific needs. OpenAI's ChatGPT has been widely recognized as a powerful conversational agent, sparking interest in how individuals and organizations can build their own models using their unique datasets. In response to this demand, Microsoft has introduced Azure AI Studio, a groundbreaking platform that empowers businesses to develop their very own AI "copilots." With Azure AI Studio, companies can now unlock the potential of AI and data, revolutionizing their operations and driving increased efficiency.

Unleashing the Power of Azure AI Studio

Azure AI Studio offers an unprecedented opportunity for businesses to harness the capabilities of AI and automate tasks such as content generation and data analysis. By training AI models using their proprietary data, organizations can ensure that the conversational agents truly understand their specific domain and are equipped to handle complex tasks with accuracy and efficiency. Gone are the days of relying on generic AI models that struggle to grasp the nuances of individual businesses. With Azure AI Studio, companies can create AI copilots that align seamlessly with their unique requirements.

Boosting Efficiency and Innovation

The introduction of Azure AI Studio marks a significant departure from traditional approaches to AI development. In the past, businesses often faced limitations when attempting to build AI models due to the lack of accessible tools and expertise. Azure AI Studio changes the game by providing a user-friendly platform that simplifies the process of building custom AI models. With an intuitive interface and a range of powerful features, businesses can now focus on innovating and driving productivity rather than getting bogged down in the technical complexities of AI development.

Breaking Through Boundaries

Azure AI Studio enables businesses to break through the boundaries that have previously hindered their AI initiatives. Whether it's automating content generation for marketing campaigns, analyzing vast datasets to extract valuable insights, or creating virtual assistants that deliver personalized customer experiences, Azure AI Studio empowers organizations to achieve new levels of efficiency and effectiveness. By integrating AI into their workflows, businesses can stay ahead of the competition and unlock opportunities for growth.

Unlock the Future of AI Customization with Azure AI Studio

The era of generic AI models is fading away, making room for a new wave of customized AI solutions. With the introduction of Azure AI Studio, Microsoft has provided businesses with a game-changing platform that allows them to build their own AI copilots. By leveraging their proprietary data and harnessing the power of Azure AI Studio, organizations can boost efficiency, drive innovation, and achieve unparalleled productivity. Say goodbye to the limitations of traditional approaches and say hello to a future where businesses can unleash the full potential of AI and data. The possibilities are endless, and the time to embrace this new era of AI customization is now.

Unlock the Future of AI Customization with Azure AI Studio

Today’s organizations need to perform complex analytics to gain insight from data and make data driven decisions. Often this means historical data from various data sources need to reference operational data. This can be a cumbersome task and can put additional load on operational databases that might already be overloaded with the transactional connectivity with live applications.

Mirroring Microsoft Fabric is a modern way to solve this analytics challenge. Microsoft Fabric is meant to be the end-to-end analytics platform for organizations. The One Lake in Microsoft Fabric is a managed storage that can store all historical and analytical data of the organization. With Mirroring, operational databases can be replicated to Lakehouse in Microsoft Fabric. Having data replicated in Microsoft Fabric, makes it easy to use it for analytics and join it with other analytical data sources to perform complex analytics like warehousing or data science.

Mirroring in Microsoft Fabric is currently available for following data sources.

1. Azure Cosmos DB

Any user created databases in Azure Cosmos DB can be replicated to Microsoft Fabric. Sample databases are not replicated in Mirroring. Currently only NoSQL API is available for Mirroring. More on limitations of Azure Cosmos DB Mirroring is available here.

2. Azure SQL

Only user created databases are replicated to Microsoft Fabric. Mirroring needs to be setup on the primary writable Azure SQL DB. Transaction log hold is maintained until the transaction is committed to both main database and Mirrored DB. More limitations of Azure SQL DB Mirroring is available here.

3. Snowflake

Native Snowflake tables are replicated in Mirroring. Tables and Columns with special characters in names are not replicated. More on Snowflake Mirroring limitations can be found here.

Below are advantages of using Mirroring in Microsoft Fabric.

1. Read and Write to Databases and Warehouse from Microsoft Fabric

Since Mirroring is a two-way replication, any writes that are done to Mirrored databases, get committed to the source database. So, Microsoft Fabric can become the single access point to manage all your databases and Warehouses that are setup for Mirroring.

2. Real-Time Data Replication

Microsoft Fabric uses the change data capture feature of source database to replicate data to Mirrored database in real time. When initial Mirroring setup is done, a snapshot of current data is taken and written to the Mirrored database. After that any changes that are committed to the source database, gets reflected in mirrored database in real time.

3. Flexible Analytics

Since the data from source databases are replicated to Microsoft Fabric Lakehouse as Delta Tables, users can use the SQL Analytics Endpoint to perform warehouse queries and reporting as well as use python and spark to perform advanced analytics and build AI models.

4. Cross-Joined Queries

Since Mirrored databases live in Microsoft Fabric One Lake, where you can have all your other analytical data and shortcuts, you can perform join of Mirrored database tables with other Lakehouse and Warehouse tables to perform complex analysis.

5. Power BI Direct Lake mode

Having data in Microsoft Fabric Lakehouse enables Power BI Direct Lake connectivity to get the best possible performance on your Power BI reports.

You can watch my Mirroring in Microsoft Fabric demo on YouTube.

Arunansu Pattanayak

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