Microsoft Fabric and GenAI, the perfect partnership to tackle business challenges

According to PWC, 44% of business leaders plan to implement data modernization by 2024 to take advantage of the benefits GenAI offers. This technology not only consumes data but also accelerates and reduces data modernization costs. As such, it will be a key part of any modern business strategy.

Microsoft Fabric can be the key tool for deploying GenAI at scale. Here’s how to use it the right way to align your data with your GenAI initiatives.  

What is Microsoft Fabric

In a previous article, we talked about the concept of Data Fabric, which refers to an architecture of services and functionalities that helps to better process volumes of data from a multitude of sources.

Microsoft Fabric, on the other hand, is a SaaS analytics solution that covers everything from data movement to data science, real-time analytics, and business intelligence.

It is a solution that offers a set of services such as Power BI, Azure Synapse, and Azure Data Factory in a single integrated environment.

Since the announcement of its preview, more than 25,000 organizations worldwide are already using Fabric thanks to its features to reshape the way teams work with data.  

It’s a unified, AI-powered platform built for the GenAI era, and here’s why you need it.

Microsoft Fabric Architecture

Before we go into detail on the cooperation that Microsoft Fabric brings with generative AI, let’s take a closer look at its architecture.

As mentioned above, Fabric combines the best of Power BI, Synapse, and Data Factory into a unified software platform with seven core workloads, each designed specifically for specific people and tasks.

With this type of unified architecture, it can reduce the typical costs and efforts of integrating analytics services and help simplify each company’s data estate. It also helps manage and protect data more effectively with end-to-end security and governance capabilities.  

The unified, multi-cloud data lake, OneLake, automatically connects to each Fabric workload and is designed to simplify data management and reduce data duplication.

Once OneLake is enabled, domains and workspaces can be used to organize your data into a logical data grid and allow everyone to search this grid using an intuitive, customizable data center. With an open data format, you only need to load data into the lake once, with the ability to use a single copy in each workload and Fabric engine, minimizing data duplication and sprawl. 

Microsoft Fabric Copilot

One of the most attractive features of Fabric is that they are building AI into each of its layers, with the goal of helping users do more things faster.

With Copilot in Fabric, you can use natural language to create data flows and pipelines, write SQL statements, create reports, or even develop ML models. But there is so much more.

In Power BI you can create reports and make narrative summaries in seconds. In Data Factory you can give instructions on how you want to ingest and transform data using natural language and Copilot will do the rest. In fact, when working in a data engineering or data science notebook, Copilot can quickly enrich, model, analyze, and explore the data.  

Microsoft Fabric to prepare your data for GenAI

GenAI can help make sense of unstructured data, such as that contained in presentations, contracts, strategy documents, customer records and so on. Some of its most popular use cases are summarising, translating, analyzing, and problem-solving, which translates into improved productivity and new services.

But in order to do all this, generative AI must have access to data that is relevant, complete, reliable, secure, and up-to-date.

One platform that can help address data challenges is Microsoft Fabric, which can align with your GenAI data and business initiatives. Some best practices for doing so include the following: 

Facilitating access to data

It is more than likely that you have data sets of different standards and in different systems. This could pose a problem for GenAI when it comes to accessing this information.

Fabric’s data lake can incorporate shortcuts that point to other storage locations, without incurring the cost, delay, and risk of moving or copying data.

With this platform, you can quickly and securely access your data in the cloud, and think about how to transition your current data lake if you have one. You may need to adapt your technology architecture, as well as assess the quality of the data, and establish some rules for how it will be indexed, governed, and distributed, among other things.  

Standardise data and keep it visible and synchronized

Once Fabric’s data lake gateways have connected your data, it is now possible for GenAI to access it.

Even if this data is in different formats, the platform will help you standardize, troubleshoot, and organize it so that your AI applications run on compatible data.

At this point, as different GenAI applications get information from Fabric and bring new data into the system, it can be kept in sync.

Platform shortcuts can also aid in the discovery of data that applications may need, meaning that teams will be able to use AI with consistent, high-quality data.  

Improving trust and optimizing data management

For there to be trust in data and the results it produces, it must be protected, troubleshot, governed, and reported on. Fabric will connect your data in a single layer, allowing you to implement cybersecurity, controls, privacy policies, and compliance.

It is also a tool with governance, reporting, analytics, and other tools designed to strengthen data quality, security, transparency, and compliance. It integrates easily with, for example, Purview.

Drives GenAI integration and business insights

Fabric has been designed to complement generative AI tools, such as Copilot and Azure OpenAI, which can leverage Fabric’s data channels for end-to-end integration.

Models will be able to get the latest, cleanest data automatically with integrated governance and monitoring as context for prompts and add-ons.

In addition, it features Power BI visuals to more attractively showcase the value that AI initiatives are delivering.

Manage costs better

Because Fabric is designed as a universal data platform, it offers ways to help you manage data-related costs. This allows you to choose different vendors to meet your storage and computing needs, use different vendors and services for different data sets, and move between them.

This increases flexibility, resulting in significant savings, especially for GenAI, which requires a lot of storage and computing resources.

Microsoft Fabric and GenAI for companies

Through the integration of LLM technology, you will be able to request the specific information you want to extract or deduce from your data, as well as understand how the code used in the different services to extract it, etc. works.

Getting started with Fabric can be overwhelming at first, which is why Plain Concepts will be your best ally. We have years of experience helping our clients create a robust and effective data strategy, and we can help you unify and secure your data so you can get the most out of generative AI in your organization.

Our experts are on hand to help you define the best path to becoming a modern, digital company, ready to tackle your strategic, operational, organizational, and technological challenges. If you want to start giving new meaning to your data and take advantage of all the benefits that AI can bring you, contact us!