Microsoft Digital stories

Editor’s note: This story was created with the help of artificial intelligence. To learn more about how Inside Track is using the power of generative AI to augment our human staff, see our story, Reimagining content creation with our Azure AI-powered Inside Track story bot.

The choices we make today regarding technology platforms shape the success or failure of critical projects in the future.

For our Employee Productivity Engineering (EPE) team within Microsoft Digital, the company’s IT organization, the challenge of choosing between Microsoft Dataverse, our low-code data platform that is part of the Microsoft Power Platform, and Microsoft SQL Server, our relational database management system (RDBMS) used for storing and retrieving data as requested by other software applications, was more than a technical decision.

It was a balancing act between empowering business users, meeting operational demands, and aligning with our company’s strategic vision for scalable, secure, and high-performing solutions.

Faced with competing priorities, the EPE team embarked on a journey to evaluate these two powerful platforms, ultimately uncovering lessons and strategies that would guide their work and inspire our enterprise customers.

The Crossroads: Business needs and technical demands

The challenge of choosing between Dataverse and SQL Server wasn’t a simple one.

“Our project requirements pulled us in two very different directions,” says Urvi Sengar, a senior software engineer on the EPE team here in Microsoft Digital. “On one hand, we wanted the low-code, rapid development capabilities of Dataverse to empower business users. On the other hand, our backend demanded high-performance querying, advanced reporting, and seamless integration with other systems.”

The team’s decision wasn’t purely technical, it was rooted in six key dimensions: low-code development, security, extensibility, cost, governance, and performance. These considerations reflected the immediate needs of the projects and the long-term goals of enabling innovation while adhering to the company’s rigorous standards for compliance and scalability.

Mapping needs to capabilities

To navigate the complexity of the decision, the EPE team adopted a structured approach. They mapped their requirements across the six dimensions and evaluated Dataverse and SQL Server based on their unique strengths:

• Low-code development: Dataverse emerged as the clear winner for user-facing applications, thanks to its seamless integration with the Power Platform. Business users can use its low-code capabilities to build apps and automate workflows without relying heavily on engineering resources. The native connectors and templates further accelerate development timelines.
• Security and compliance: While both platforms offered robust controls, Dataverse’s role-based access and encryption—tightly integrated with the Microsoft cloud ecosystem—simplified compliance for business-centric apps. SQL Server, however, provided the granular control needed for systems handling sensitive or regulated data.
• Extensibility: The team found that Dataverse worked best for apps staying within the Power Platform ecosystem, while SQL Server excelled in complex backend operations and external integrations.
• Cost and governance: Dataverse’s licensing model was cost-effective for smaller-scale applications but became expensive at scale. SQL Server, with its mature governance models, offered predictable costs and reduced operational overhead when integrated into existing infrastructure.
• Performance and scalability: For data-intensive applications requiring real-time exports and complex joins, SQL Server’s ability to handle large datasets and optimize queries made it the superior choice.

The team didn’t rely on a single framework to evaluate the platforms—they blended the power of several tools together.

“We combined internal benchmarks, stakeholder interviews, and scenario-based analysis,” Sengar says. “The decision wasn’t binary—it was contextual, tailored to the unique needs of each project.”

Context-driven choices in action

The team’s thoughtful evaluation process came to life in two key projects, each showcasing the strengths of one platform over the other.

Dataverse was chosen as the data backbone for the Customer Validation Power App—a user-facing Power App designed to validate customer data. Its low-code capabilities and seamless integration with the Power Platform means that business users can use it to validate customer data, synchronize updates, and maintain compliance with Microsoft’s policies. They can also use the app to independently manage app features, which helps accelerate development cycles and reduce reliance on engineering resources.

“Dataverse is a game-changer for business-centric, low-code solutions, while SQL Server remains a cornerstone for high-performance, data-intensive applications.”

Urvi Sengar, senior software engineer, Microsoft Digital

In contrast, SQL Server proved indispensable for backend systems requiring high-performance querying and advanced analytics. By using SQL Server’s structured data control, computed columns, and user-defined functions, the team delivered real-time analytics and secure access management for sensitive data.

“SQL Server handled complex workloads with predictable performance, enabling us to integrate with external systems and legacy applications seamlessly,” Sengar says.

It came down to having to choose between two good options.

Looking ahead: A balanced approach to innovation

The EPE team’s work demonstrates the power of a contextual, thoughtful approach to technology selection. By understanding the strengths and trade-offs of both Dataverse and SQL Server, they not only delivered successful projects but also established a model for future decisions.

“The key takeaway for us was that the right choice depends on the specific context,” Sengar says. “Dataverse is a game-changer for business-centric, low-code solutions, while SQL Server remains a cornerstone for high-performance, data-intensive applications.”

As we continue to innovate here in Microsoft Digital and across the company, the lessons from our journey can serve as a guide for other teams navigating the complexities of platform decisions. By sharing their story, the EPE team hopes to inspire our enterprise customers to embrace a balanced approach to innovation, using the best of both worlds to achieve their goals.

Key takeaways

The EPE team’s journey revealed key lessons and best practices that other IT teams can apply:

• Context is everything: Dataverse and SQL Server serve different purposes, so your choice between the two should align with the specific needs of your application, user base, and operational goals.
• Don’t underestimate governance complexity: While Dataverse simplifies some aspects of governance, SQL Server offers granular controls that are critical for compliance-heavy systems.
• Integration isn’t always seamless: Testing real-time data flows early is essential to avoid surprises later, particularly when integrating Dataverse with external enterprise systems.
• Developer readiness matters: A successful transition to Dataverse requires investments in training and community engagement to ensure smooth adoption.
• Evaluate, align, and pilot: Among the best practices, Urvi highlights the importance of using a decision tree or framework to evaluate platform fit, aligning stakeholders early to surface hidden requirements, and running pilots before scaling to validate assumptions and uncover edge cases.

Try it out

• Get started with Dataverse and sign up for a free trial of Microsoft Copilot.
• Learn more about SQL Server 2025.

Related links

• Explore the Microsoft Dataverse documentation.
• Learn more about the Microsoft Power Platform.
• Explore educational SQL resources.
• Read more on SQL Server technical documentation.

We’d like to hear from you!

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post How our team chose between Dataverse and SQL Server appeared first on Inside Track Blog.

To stay ahead, we are continuously exploring ways to use technology to drive efficiency and value. One way we’re innovating is by using generative AI to accelerate content development for our Inside Track blog.

While there will always be humans in the loop, using generative AI, we have embarked on a journey to revolutionize how we engage with our customers through compelling stories and case studies. In fact, this very article was created with the help of Artificial Intelligence.

The vision and challenge

The vision for this project was clear: use AI to accelerate content creation, reduce turnaround times, and enable any member of our Microsoft Digital team to quickly share their story with customers. However, the path to realizing this vision was not without its challenges.

“We were venturing into uncharted territory, using AI in its infancy with a limited budget and few resources,” says Dwight D. Jones Sr., a principal product manager on the Frictionless Device team who led the initiative.

To overcome these challenges, the team created a pitch deck based on their vision, built a detailed technical specification, and worked with stakeholders to build support for the project. They formed a virtual team across the Microsoft Digital Inside Track team, the Frictionless Devices team, and the Employee Productivity Engineering team.

With the approval of Microsoft Digital leadership, they launched a small proof of concept that proved successful—the Inside Track content bot. In the pilot, the team was able to use an AI-powered interview bot to produce excellent first drafts of blog posts, saving significant time per story. 

Accelerating publication and reducing costs 

Senior Director Keith Boyd emphasized the dual challenge of telling more stories at a lower overall cost and accelerating publication.

“The key technology that’s powering the bot is OpenAI on Azure,” Boyd says. “It’s already helping us, by making it easier for subject matter experts in Microsoft Digital to share their expertise on their own schedule.” 

By using the bot, the team hopes to increase the number of stories in the pipeline and decrease the time it takes to reach publication.

“Our primary metric is time to publication,” Boyd says. “Can the bot help us move from a six-week cycle for story production to end-to-end story authoring and publication in half that time?” 

Streamlining the process 

Revanth Chandra Pydimarri, a senior product manager on the Inside Track content bot virtual team, highlighted the need to streamline the drafting and publishing process.

“We were wasting resources through inefficient operational processes, and it took a lot of time for us to reach out to relevant subject matter experts, get the content from them, write the story, and eventually publish it,” Pydimarri says. 

The team turned to Microsoft Azure AI, building a bot that uses generative AI capabilities—including Retrieval-augmented generation (RAG) and Azure OpenAI—on your data to interview subject matter experts (SMEs) at their convenience.

“We have trained the bot in the style of Inside Track,” Pydimarri says.

The results were impressive, with a time savings of at least five hours per story, while maintaining publication standards.

Capturing input and maintaining style 

Urvi Sengar focused on training the bot how to write stories with the same look and feel of human-written stories, and on how to use the bot to capture input from SMEs and turn it into content. The bot was trained using a comprehensive dataset of previously published stories and with writing guidance provided by the editorial team, enabling it to emulate the Inside Track team’s storytelling style.

 “The bot’s sophisticated content summarization and curation techniques allow it to draft high-quality stories quickly, maintaining the nuanced details and tone provided by the SMEs,” says Sengar, a senior software engineer in Microsoft Digital. 

Despite the challenges of transferring subject matter expertise and iteratively improving the process based on user feedback, the project has been well received by stakeholders.

“The bot is now able to generate drafts that are more than 70% complete, significantly reducing the time required to produce stories,” Sengar says.

The team is adding the ability for the bot to verbally interview SMEs by integrating VoiceRAG using Azure AI Search for audio to text capabilities. This will enable the bot to transcribe spoken interviews accurately and efficiently, streamlining the content collection phase and creating richer, multi-dimensional stories through a more natural interviewing process.

Combining multiple perspectives 

Lukas Velush, the managing editor of Inside Track, tackled the challenge of using an AI-powered bot to interview multiple SMEs and combine their interviews into one coherent story.

“Our challenge was to continue telling the stories of our subject matter experts across Microsoft Digital, despite having a smaller team and a shrinking budget,” Velush says.

This downward pressure on resources was the inspiration for the bot, which could help create stories at a lower cost and at a faster pace. 

The bot is designed to emulate human writers, interviewing SMEs about their IT work, their challenges, and how they overcame them.

“One of the biggest challenges that we’re still working on is getting the bot to be able to interview multiple people for a story then weave what each person has to say into a coherent narrative,” Velush says.

The current solution is having the bot interview each person separately, then combine the resulting stories into one comprehensive narrative. 

The initial results are promising, with bot-written stories costing 50% less than human-written stories and being completed at least 30% faster.

“This has been an amazing journey—we’ve learned a ton about AI, about humans, and about what it takes to report and write stories like this,” Velush says. “I see the bot as a great helper that can work right alongside our human writers.” 

The future of AI-driven content creation 

As Microsoft Digital continues to innovate and push boundaries, the Inside Track bot stands as a testament to the power of AI to transform the way we tell our stories. Using AI, the team has shown that it can accelerate the content creation process, enabling delivery of high-quality, engaging content faster and more efficiently than before. 

Looking ahead, the team plans to further enhance the bot’s capabilities. Jones shared that the team plans to use AI to produce multiple types of content with a single entry, such as articles, blog posts, PowerPoint decks, and white papers. They also plan to generate content in multiple languages and to support readers with accessibility needs. 

Boyd emphasized the potential for AI to augment human capabilities.

“One goal is to reassure other content teams that AI-powered bots are not here to replace them, but to augment their capabilities and make them more productive,” he says.

This is just the start.

“This is V1,” Pydimarri says. “We have plans to add more features and also expand the functionality to accommodate other team’s requirements, too.” 

Future enhancements will focus on expanding the bot’s capabilities and functionality. “That will ensure it continues to meet the evolving needs of the Inside Track team and other users,” Sengar says.

Looking to the future

Using AI to accelerate content creation in Microsoft Digital exemplifies the team’s innovative spirit and commitment to customer engagement.

“This project is just the beginning,” Jones says. “We’re excited about the potential of AI to revolutionize how we engage with our customers and look forward to seeing where this journey takes us.” 

The Inside Track bot has demonstrated the potential of AI to streamline processes, improve efficiency, and deliver high-quality, engaging stories that resonate with the audience. It’s a great example of digital transformation in action, paving the way for future innovations. 

As we continue to push the boundaries of what’s possible with AI, we invite you to join us on this journey. Explore the capabilities of the tools and technologies available through Microsoft Azure AI in your own content creation processes and see firsthand how it can enhance productivity and storytelling quality. 

We’re using AI to accelerate content generation at Microsoft, and you can too. Here are some highlights from our journey:

• AI-powered content creation: Microsoft Digital is using generative AI to automate content creation for the Inside Track blog, significantly reducing turnaround times.
• Successful pilot: The AI-powered chatbot proved successful in a pilot, producing excellent first drafts of blog posts and saving significant time per story.
• Efficiency and cost reduction: The initiative aims to tell more stories at a lower overall cost and accelerate publication, with Inside Track content bot-written stories costing 50% less and being completed at least 30% faster.
• Streamlined process: The AI bot interviews subject matter experts (SMEs) at their convenience, eliminating the need for coordinating schedules and saving at least five hours per story.
• Maintaining quality: The bot is trained to emulate the Inside Track team’s storytelling style, capturing nuanced details and tone provided by SMEs.
• Adding voice: We’re integrating Azure AI Speech Studio for audio-to-text capabilities, which will make getting interviewed by the Inside Track content bot a more natural experience for our SMEs.
• Future enhancements: We’re expanding the bot’s functionality to help other Microsoft Digital teams.

• Learn how to use Microsoft Azure OpenAI at your company.
• Learn more about Microsoft 365 Copilot.

• Read our guide for deploying and driving adoption of Microsoft 365 Copilot here at Microsoft.
• Find out how we’re tackling Microsoft 365 Copilot governance internally at Microsoft.
• Learn how we’re becoming an AI-first Frontier Firm.
• Check out how we’re embracing AI-powered agents internally here at Microsoft.

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post Reimagining content creation with our Azure AI-powered Inside Track story bot appeared first on Inside Track Blog.

Just like it is for all large enterprises, maintaining accurate and secure group memberships enables our employees to collaborate effectively while also safeguarding our sensitive information internally here at Microsoft.

The Microsoft Group Membership Management (GMM) tool addresses this challenge head-on by providing a robust solution that simplifies group membership management while enhancing security and productivity across Microsoft. Initially developed to solve a challenge within Microsoft, GMM is now available on GitHub, giving other organizations to access to its capabilities.

The need for group membership management 

GMM was designed to address two critical issues that companies like ours face: 

• Collaboration barriers: When the right people aren’t in the group, collaboration tools are less effective.
• Security risks: When individuals retain access to groups unnecessarily, organizations face potential data exposure.

“One of our main priorities was to create a solution that balances seamless collaboration with stringent security,” adds Olivia Han, senior product manager for GMM. “We wanted organizations to feel confident in their group memberships while making the process as intuitive as possible.”

Key features of GMM 

GMM is a multi-source, multi-destination membership synchronization tool. It enables organizations to define group memberships based on user information from multiple sources and project those memberships into groups and even Microsoft Teams channels. Its standout features include: 

• Flexible membership definition: Membership can be defined based on organizational structure, user attributes, and exclusionary rules. Depth limits ensure precision and control. 
• Empowered group ownership: Group owners can define and manage their memberships independently, while administrators retain tools to protect sensitive HR information. 
• Change threshold protection: To prevent accidental disruptions, GMM includes increase and decrease thresholds that require owner confirmation before large-scale membership changes. 

Development journey and challenges 

GMM began as a solution to project nested security group hierarchies into flattened Microsoft 365 groups, addressing the lack of native nesting support in Microsoft 365. Over time, the tool evolved into a comprehensive solution that uses a variety of Azure services, including Storage, Service Bus, SQL, Azure Data Factory, and Key Vault, among others. 

“We’ve been laser-focused on adopting Microsoft Secure Future Initiative best practices,” says Paul Daly, a principal software engineering manager for GMM in Microsoft Digital. “Eliminating secrets, adopting managed identities, and moving resources to private networks have significantly improved our security posture. Scalability has been another ongoing focus, with innovations like a ‘multi-lane’ process to handle large membership changes without delays.” 

Impact and integration 

Internally at Microsoft, GMM has simplified maintenance for thousands of groups.

“Automating user additions increased the use of collaboration tools like Viva Engage, Teams, and Outlook groups,” Han says. “Removing unnecessary access not only boosts security but also gives us the confidence to enable features like Copilot.” 

GMM has had a significant impact on personalizing and enhancing the employee experience at Microsoft. By managing groups based on tenure, GMM enables targeted content delivery on the intranet website and HR portal via Viva Connections, providing relevant information to new employees during their crucial onboarding period. 

“Based on what our internal customers have told us, we know that GMM has eliminated days and even weeks of manual work that our business admins have to do to maintain accurate groups rosters,” Han says. “It has also mitigated security concerns, including reducing the risk of oversharing.” 

Externally, organizations that have adopted GMM from GitHub have experienced similar benefits, and their feedback has driven continued improvements. 

GMM integrates seamlessly with Entra ID groups and Team channel memberships, extending its impact across the Microsoft 365 suite, including Viva Engage, Teams, Outlook groups, Viva Connections, and CoPilot. 

Looking ahead 

The future of GMM is bright, with enhancements focused on usability, performance, and deployment: 

• Improved user interface: Updates driven by internal and external feedback reduce admin effort and empower users. 
• Enhanced scalability: The multi-lane process ensures timely completion of membership changes, even during large onboardings. 
• Simplified deployment: Streamlining installation will make GMM more accessible for external organizations. 

“We hope GMM’s features resonate with organizations and their use cases,” Daly says. “If so, we encourage them to give it a try and share their feedback via the GitHub repository.” 

GMM exemplifies how Microsoft uses its own tools to solve real-world challenges and shares those solutions to help others achieve their goals. With its powerful capabilities and user-centric design, GMM is transforming the way organizations manage group memberships, fostering both collaboration and security.

Here are some tips for rethinking group management at your company:

• Simplified group management: GMM streamlines group membership management, enhancing both security and productivity across organizations.
• Addressing key issues: GMM tackles collaboration barriers and security risks by ensuring that the right people are in the right groups and removing unnecessary access.
• Robust features: GMM offers flexible membership definitions, empowered group ownership, and change threshold protection to prevent accidental disruptions.
• Development and scalability: Initially created to solve internal challenges, GMM has evolved into a comprehensive solution using various Azure services and focusing on scalability and security.
• Impact and future enhancements: GMM has significantly improved group management at Microsoft with ongoing enhancements aimed at usability, performance, and deployment.

Learn more on how to manage your groups.

• Find additional resources for Group Membership Management on GitHub.
• Learn more about Group Membership Management (GMM).
• Unpack how Microsoft automates Group Member Management.

• Want more information? Email us and include a link to this story and we’ll get back to you.

The post Streamlining group membership management and governance at Microsoft appeared first on Inside Track Blog.

In the rapidly evolving world of cloud services, managing technical subscriptions can become a daunting task. At Microsoft, we faced a similar challenge—Microsoft Azure subscription sprawl.

“If customers don’t have a formal system in place to manage their Azure subscriptions, it can lead to subscription sprawl,” says Trey Morgan, a principal product manager on our Microsoft Digital Azure Optimization team. “This can cause potential legal and security risks.”

Our solution?

The Azure Information Request System (AIRS).

The impact of AIRS has been significant, particularly in governance and cost management. By assigning subscriptions to the business hierarchy from day one, they don’t get lost in a company of our size. We can quickly identify who to contact for security issues, cost issues, and understand how these cloud resources fit into Microsoft’s business.

— Trey Morgan, principal product manager, Microsoft Digital Azure Optimization team

AIRS streamlines the process of setting up new Azure subscriptions.

“AIRS is an internal system we’ve developed that offers a solution to govern and track subscriptions, a strategy that Microsoft has effectively used,” Morgan says.

Users requesting a new subscription fill out a form detailing cost assignment and ownership. The system also helps assign the subscription to our business hierarchy, providing visibility on where the cloud resources fit within the company.

“The impact of AIRS has been significant, particularly in governance and cost management,” Morgan says. “By assigning subscriptions to the business hierarchy from day one, they don’t get lost in a company of our size. We can quickly identify who to contact for security issues, cost issues, and understand how these cloud resources fit into Microsoft’s business.”

We’ve also integrated AIRS with tooling that benefits several different parts of our business.

“Azure governance, security, finance, and leadership all benefit from AIRS,” Morgan says. “Without it, we would lack crucial information about these Azure subscriptions or why they exist.”

Azure subscription sprawl strategies

To prevent subscription sprawl in your Azure environment, consider implementing the following strategies:

• Consistent landing zones: Establish consistent landing zones based on application archetype subscription strategies. This approach minimizes the growth of subscriptions by providing predefined structures for different types of workloads.
• Requisite components definition: Expand the definition of requisite components to better align with the governance and compliance needs of a mature cloud enterprise. Clearly define what components are necessary for each subscription, ensuring that they meet organizational standards.
• Subscription policies: Control the movement of Azure subscriptions out of the current directory and into it. Global administrators can allow or disallow users from changing the directory of an Azure subscription. For specific scenarios, configure a list of exempted users who can bypass the policy settings that apply to everyone else.
• Restrict self-service subscriptions: Disable self-service purchases to prevent standard users from creating subscriptions without proper authorization.

Remember that effective governance and clear policies play a crucial role in managing subscription sprawl and maintaining a well-organized Azure environment. As we continue to evolve and improve AIRS, we hope our journey can provide valuable insights for other companies navigating their own cloud subscription challenges.

The future of AIRS

Having a company operating model and policies is effective and IT leaders need to adhere to them and regularly review cloud subscriptions and usage to use them for the greatest security, flexibility, and output value. As we look to the future, we’re confident that AIRS will continue to evolve and provide even greater benefits to the company.

Consider using a system like AIRS to streamline the process of setting up new Azure subscriptions and assign them to the business hierarchy. Here are some tips on how you can get started at your company:

• Establish consistent landing zones based on application archetype subscription strategies to minimize the growth of subscriptions.
• Expand the definition of requisite components to align with the governance and compliance needs of a mature cloud enterprise.
• Control the movement of Azure subscriptions in and out of the current directory by setting subscription policies.
• Disable self-service purchases to prevent standard users from creating subscriptions without proper authorization.
• Remember that effective governance and clear policies play a crucial role in managing subscription sprawl and maintaining a well-organized Azure environment.

Create your Microsoft Azure free account today.

• Learn more about managing resources with Azure PowerShell.
• Unpack Azure Resource Manager in an overview.
• Discover revolutionizing SAP and ADP connectivity with Microsoft Azure VWAN and VPN.

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The post Creating a manageable Microsoft Azure subscription model appeared first on Inside Track Blog.