Top five ways data is the fuel that powers IT at Microsoft

At Microsoft Digital, our mission is to transform the digital employee experience across devices, applications, and hybrid infrastructure.

But what fuels that transformation?

Data.

Enterprise data, backed by a strong strategy and culture, powers the technologies that drive Microsoft forward.

Let’s explore some of the ways data is the fuel that powers IT at Microsoft.

Modernizing our corporate functions

In the era of AI, data plays a crucial role in our effort to modernize corporate functions like Human Resources, Finance, and Corporate, External, and Legal Affairs (CELA). For instance, employees can use our Employee Self Service (ESS) agent to retrieve information and insights in real time using natural language queries. In the past, these actions were either conducted manually or required an IT support ticket, both of which resulted in a negative user experience. Now, employees can use ESS to complete their tasks more efficiently and with the confidence that the data they’re working with is secure.

Another impact of the powerful combination of data and AI is being realized by HR generalists. The Microsoft HR Business Intelligence team manages an immense number of Power BI dashboards. Instead of manually sifting through vast amounts of information to locate required data, our Microsoft Digital team has developed new capabilities that allow HR generalists to use natural language queries to find the Power BI dashboards they need in real time. These tools use generative AI to optimize the time employees spend searching for information, so they can focus on their strategic deliverables.

“AI is not just about algorithms—it’s about the data that powers them. A well-structured enterprise data strategy ensures that AI can drive automation, insights, and business transformation at scale. At Microsoft Digital, we’re using data to redefine how employees work and innovate,” says Faisal Nasir, a principal architect in Microsoft Digital.

In Microsoft Digital, we’ve defined a data standard for our AI workloads that we refer to as “AI-ready data.” AI-ready data is data that’s available, complete, accurate, and high quality. AI-ready data allows tools like Microsoft Fabric for data management and Microsoft Purview for governance make the most of AI tools and machine learning for the company’s corporate functions. By using data mesh, a decentralized data architecture approach, data scientists and engineers build data products across organizational siloes, or workspaces, using the One Lake feature of Fabric, illuminating cross-domain insights. By using Purview’s Shortcut feature, engineering teams can more easily request and receive approval for access to the information they need to manage their organization more effectively and efficiently.

In the race to adopt machine learning and AI, organizations often focus on model sophistication while ignoring the foundation: the data. Without clean, labeled, contextualized, and well-governed data, even the most advanced algorithms will falter. AI-ready data isn’t just nice to have—it’s the make-or-break factor in every successful AI initiative. Models trained on poor-quality data will amplify bias, hallucinate patterns, and make dangerously flawed predictions. Meanwhile, organizations that invest in high-quality, AI-ready data gain not just better models, but a long-term competitive edge. They build systems that learn faster, adapt better, and scale smarter. In short, AI-ready data isn’t the backend. It is the strategy.

“AI is only as smart as the data it’s fed—and if that data isn’t AI-ready, you’re not building intelligence, you’re building illusions,” says Patrice Pelland, a partner engineering manager in Microsoft Digital.

{Learn how we’re transforming our data governance at Microsoft with Microsoft Purview and Microsoft Fabric.}

Optimizing our employee experience

Microsoft Digital’s user-centric, coherent design philosophy puts the user—an employee or a guest—at the heart of every decision and aligns all our facility’s services—physical and digital—to the needs of people. We employ a data-driven approach to the employee experience, using AI to aid in decision-making, improving how Microsoft employees interact with technology, physical spaces, and other Microsoft resources.

A few examples of how we’re using data and AI to improve the employee experience include:

Commute optimization: AI is being used to predict the best routes and Connector buses for employees, improving their commute experience. Microsoft Digital observes frequency and travel patterns to predict and recommend optimal routes to the desired destination, thereby decreasing the amount of time spent in transit.

Dining solutions: Microsoft Digital is actively working to enhance the dining experience through the integration of AI capabilities. We’re enabling insights based on data related to dining popularity—essentially, where and what do employees like to eat? By using AI and machine learning, we aim to offer a richer Copilot experience to users. For instance, we’re developing features that analyze cafe station popularity over time, and calculate the average fulfillment times for orders at each station. With this data, employees can use Copilot to make informed decisions about where to dine based on real-time insights into station capacity, foot traffic, and average efficiency.

Occupancy predictions: Predicting employee occupancy in on-campus facilities helps to optimize utility usage. By using AI and machine learning to understand footfall patterns, the team can adjust heating and cooling systems to save energy and improve efficiency.

{Learn more about our fresh approach to accessibility powered by inclusive design.}

Managing our network infrastructure

Managing Microsoft’s network infrastructure effectively is crucial for maintaining productivity and collaboration. A data-driven approach can provide the necessary insights and tools to ensure a seamless connectivity experience, efficient diagnostics, performance and cost optimization, and proactive security management.

Pillars of data transformation

The Infrastructure and Engineering Services team (IES) in Microsoft Digital has a close partnership with our data engineering team to transform network infrastructure IT. A consolidated data lakehouse delivers data on inventory, configurations, health, device hardware and software compliance, vulnerability analytics, and more. The data platform supports an ecosystem of data citizens (network engineers, site operators, and security engineers) to self-serve on monitoring, dashboards, and diagnostics. The same data lakehouse enables applications to build rich network visualizations, implement AIOps to automatically manage incidents, and deliver network dedicated AI agents.

The IES data team also plays a crucial role as Customer Zero for Microsoft’s data analytics and governance products, like Fabric, Purview, and Copilot. Their contributions to testing and providing feedback are invaluable for the development and improvement of these products:

• Using language models to automate the creation of descriptions of data schemas, reducing the time required to publish data products into the Purview catalog.
• Developing Copilot agents that transform natural language prompts into Kusto Query Language (KQL) queries, further increasing the accessibility of the data for IT technicians and business owners. KQL is a powerful tool used to query structured, semi-structured, and unstructured data.

“Global connectivity—connecting all employees globally and ensuring they can access necessary resources from wherever they are—is our foremost priority on the Infrastructure Engineering Services team,” says Oana Nica, a principal group engineering manager in Microsoft Digital.

Data-driven security

Security in the era of AI is more challenging than ever given the increasing scope and frequency of cybersecurity attacks and the sophistication of threat actors. The investigation by the US Department of Homeland Security’s Cyber Safety Review Board (CSRB) regarding the Storm-0558 cyberattack, from summer 2023, emphasized the severity of the threats facing our company and our customers. Managing the security of a digital landscape with the breadth and complexity of Microsoft is our top priority.

The Secure Future Initiative (SFI), a company-wide effort aimed at addressing security issues across Microsoft involves multiple organizations and requires a coordinated effort to manage and track progress. Data management plays a critical role in the success of SFI. A data-driven approach to security management can provide the necessary insights and tools to ensure compliance and prompt attention to security concerns.

One of SFI’s key components is providing data views for leadership. These data views help leaders understand the status of their organizations, identify areas that need attention, and make informed decisions. Microsoft Digital has built tools using Azure DevOps to ensure that leaders have the necessary insights to manage security effectively. Additionally, creating a reporting structure to track progress and compliance is essential for managing security initiatives. A transparent, common-sense structure combined with high-quality data helps ensure that initiatives are completed on time and that any exceptions are managed effectively.

Improving culture with data

In Microsoft Digital, we’re fostering an environment that prioritizes data quality and effective governance. Central to that effort is our system of continuous improvement (CI), an operating model that enhances our products, services, and processes with the goal of achieving improved efficiency, quality, and overall performance over time. In the realm of data and AI, CI is integral to fortifying data integrity, accelerating model development, and enabling data-driven decision-making at scale. By embedding dynamic feedback loops into our workflows, we can adapt rapidly to evolving business needs, mitigate risks, and maximize the value of our AI investments.

Building a robust culture that emphasizes transparency, accessibility, and continuous improvement is imperative for our organization to maximize the value of AI. Our Microsoft Digital Data Council creates curricula and sponsors learning activities to equip our employees with the skills required to thrive in a data and AI-centric world. The curriculum includes high-level courses on data concepts, applications and extensibility of AI tools like Microsoft 365 Copilot, in addition to data products like Microsoft Purview and Microsoft Fabric.

“At Microsoft Digital, we recognize that a strong data culture is essential to engineering excellence and AI-driven innovation,” Nasir says. “Through architecture community discussions, we focus on robust design, governed data products, and scalable, AI-ready solutions. By embedding a design-first mindset and continuous improvement into our data strategy, we regularly assess, refine, and evolve our practices. This iterative approach empowers informed decisions, drives efficiency, and unlocks ongoing innovation.”

With a better understanding of the impact a strong data culture can have on productivity and continuous improvement, Microsoft employees not only drive the AI transformation, but also gain insights into their organization’s cultural dynamics and make informed decisions to foster a positive and inclusive environment.

{Learn how we’re responding to the AI revolution with a Center of Excellence.}