The future of AI promises to drive new ways of working, reinventing the experience for everyone from data engineers to business users and CIOs. AI can mean broad-scale transformation, especially in the data foundation layer, an intrinsic part of how organizations run and grow. At the latest Microsoft Ignite conference, leaders could see how a GenAI-powered IT function could position them well to scale across the business for productivity and more. Here are three insights around Microsoft Fabric coming out of the conference to get your data and GenAI initiatives started.
1. Enable AI-powered productivity
Fabric has AI weaved into every aspect of its design and built it into every workload. Teams working with data, authoring code, or creating reports can use GenAI to do their job faster. For example, when using Data Factory to do ETL-ingesting, build data pipelines, and transform data with data flows, AI enhances the capabilities of Microsoft Fabric, where users can use natural language to simplify tasks. Or, if you’re working with Data Warehouse, taking data that’s landed in OneLake, building a data model, and writing out T-SQL queries, AI will make intelligent suggestions and fixes while you are coding.
2. Show (rather than tell) your business potential
Another transformative capability covered at the conference is Copilot’s integration with Power BI, which automates the creation and refining of visualizations and dashboards. Using dynamic querying, users can apply filters, identify relevant metrics, or perform on-the-fly calculations. It can suggest additional metrics to analyze based on patterns it identifies in the dataset and proactively alerts you to potential anomalies, risks, and opportunities, such as revenue dips or underutilized assets. For CIOs looking to translate GenAI’s value transparently, this automatically turns your data into valuable insights any business user can understand without needing knowledge behind the technical structure of the dataset.
3. Make insights accessible & actionable
What if you could query multiple data sources, reason across them, encapsulate that domain knowledge, and then maintain that conversational history and context? Microsoft’s developments with AI Skills, its virtual data agent, is evolving to become that expert. Take, for example, a company that wants to answer the question: “Which of our top customers experienced delays in deliveries this quarter?” They will be able to develop an AI Skill for customer analytics that will draw loyalty data from a semantic model, sales data from a data warehouse, and delivery information from a real-time KQL database to draw the answer in the near future. AI Skills can also explain their reasoning and actions, increasing trust and transparency. Let’s say a user queries the agent about sales trends; the agent will then explain that it analyzed transactional data from the past year, correlated with customer demographics, and identified seasonal patterns.
One Customer’s Transition to Microsoft Fabric
Advancement depends on data, but it also depends on the right technology to support uncovering insights. An academic medical center, found its potential limited by obsolete and expensive on-prem hardware. They wanted to operationalize and unify their organization’s data sources on a shared, scalable SaaS foundation while gaining HIPAA protections and governance across all user experiences. Fabric provided that experience, democratizing their data while enhancing reliability, time to insights, and advancing mission-critical priorities.
Get started with Microsoft Fabric
Microsoft Fabric brings all your data sources together into one seamless platform, making data management straightforward and ensuring your data is clean, consistent, and ready for AI applications. This unified approach unlocks your potential to harness AI, boosting productivity and uncovering new business opportunities. 3Cloud’s extensive experience helping clients realize the full potential of their Azure platform and Fabric capabilities can help you accelerate your AI journey and quickly move from proof of concept to realizing value.
