A decade ago, we faced the same issues with document sharing. Sharing documents with your coworkers meant emailing attachments or managing files on local network drives. Then, cloud services like OneDrive and Dropbox transformed document sharing and collaboration by providing a single, accessible home for files. In the data realm, a similar transformation is happening now with OneLake.

Instead of the patchwork of storage accounts and ad-hoc data marts scattered across departments, organizations need a single, unified access point for all their data. Now with Microsoft OneLake, we have the solution. With OneLake, you can access your entire multi-cloud data estate from a single data lake that spans the entire organization. Similar to how OneDrive is wired into all your Microsoft 365 applications and provides a convenient storage location, OneLake acts as the central, accessible location for comprehensive data access and management.​

In this blog post, we’ll explore why OneLake is the ideal data lake to unify your data estate and help you create AI applications, focusing on five key pillars: breaking down silos, connecting to all your data, working from a single data copy, discovering and managing in a data catalog, and sharing data with granular security.

Breaking down siloes with a unified data foundation

Traditionally, every department, team, and even project in an organization creates their own siloed data stores to maintain data ownership and granular control over security and compliance. The result, however, is a fragmented patchwork of ‘data islands’. This siloed system can’t keep up with fast paced data projects, especially as frontier firms start deploying agents across the organization that need access to cross-department data.

Instead, you can deploy OneLake as the central data access point for the entire organization. Every Microsoft Fabric tenant comes with just a single OneLake instance, with no additional infrastructure to manage. Every department, team, and project can store or connect their data to a single unified data lake and then use a system of Fabric domains, sub-domains, and workspaces—each with their own administrator—to organize their data into a logical data mesh. This system maintains data ownership and allows for federated governance while ensuring authorized users can discover and use data from other domains without friction. Watch this video to see how you can set up your own logical data mesh in OneLake:

By consolidating data access to one place, OneLake dramatically simplifies data sharing and integration. When a data project requires data from multiple departments, users can query and combine data from multiple domains directly in OneLake rather than requesting exports or setting up complex pipeline jobs. And OneLake’s reach isn’t limited to Azure, it can virtualize data from across your other clouds and will appear just like any other data item in OneLake.

Connect to any data, anywhere without duplication

With your data mesh in OneLake organized, you then have the tools to connect to all of the data sources in your data estate. Most data estates naturally span multiple clouds, accounts, databases, domains, and engines, and data professionals spend half their time trying to connect data sources to incompatible platforms or updating their out-of-date data with complex data pipelines. With OneLake, we’ve simplified how you bring data in with a zero-copy, zero-ETL approach with two key Fabric capabilities: shortcuts and mirroring.

OneLake shortcuts enable your data teams to virtualize data in OneLake without having to move and duplicate it. They act essentially as metadata pointers, similar to a shortcut on your desktop. This capability is particularly adept at helping you break down siloes across your data estate and even between OneLake domains. You can create shortcuts to data which lives in another domain or workspace, while ensuring only one copy of the data exists. Shortcuts even preserve data ownership and governance across domains, meaning if you update your data item or restrict access to it, all users who’ve bypassed to the data will instantly see the change. With shortcut transformations, you can even apply automatic changes to the data like converting the data format or removing PII data. We have shortcuts available for OneLake, Azure Data Lake Storage, Azure Blob storage, Amazon S3 and S3 compatible sources, Iceberg-compatible sources, Microsoft Dataverse, on-premises sources, and more on their way.

You can also use mirroring, a no-ETL experience to add proprietary databases or data warehouses to Fabric. Depending on the data source, mirroring can either replicate the entire database or just the metadata in OneLake in Delta Parquet tables and keep the data in sync in near real time. We currently have Mirroring enabled for Azure Cosmos DB, Azure SQL DB, Azure SQL MI, Azure PostgreSQL, Azure Databricks Unity Catalog, Snowflake, and many more sources coming soon including SQL Server, SQL Server 2025, Oracle, and Dataverse. With Open Mirroring, you can even create custom mirroring experiences for your own applications.

Check out this quick demo of these features in action:

The benefits of these innovative, no-ETL options are massive. No more cumbersome ETL pipelines, no more sprawling, out-of-date copies of the data, and no more data siloes across every part of your business. Once your data is connected to OneLake, you only need a single copy across every engine.

Collaborate on a single copy of data with open formats

When we built OneLake and the Fabric engines, we designed them to support open data formats, standardizing on both the Delta Parquet and Apache Iceberg formats. This commitment to common open data formats means that you need to load your data into OneLake once and all the Fabric engines can operate on the same data, without having to separately ingest it. Having only one copy of the data means teams can collaborate on a single source of truth rather than fragmenting information into endless copies in each stage of the analytics journey.

Creating multiple copies of the same data not only wastes storage space but also leads to version mismatch. By eliminating redundant copies, OneLake ensures everyone is working from the most up to date version of the data without refresh delays or manual syncs. Instead of marketing and finance creating separate copies of a lakehouse with customer revenue data, they can work from the same data with different metadata, filters, and BI reports added. IT teams can spend less time maintaining complex pipelines and admins only have one copy to manage with far easier audit trails to follow. Moreover, data professionals can easily pick the engine they most prefer, whether its T-SQL or Spark, knowing all the engines are optimized for Delta Parquet and will work from the same copy.

Everyone operates on the same single version of truth, from a data scientist training a model to an executive reviewing a dashboard, driving a more aligned and efficient organization.

Discover, manage, and govern in a complete catalog

Minimizing data duplication and sprawl also requires ensuring the right people can find and explore the right data. The benefits of a data culture have been clear for years, but with generative AI the potential business impact is increasing exponentially. Frontier firms are already using AI assistants and building custom agents to transform how their teams interact with data from technical professionals creating data items and drafting code to business users quickly answering their pressing data questions. But crucially, this culture requires that everyone has the ability to discover high quality data.

That’s where the OneLake catalog comes in. We’ve designed the OneLake catalog to be the single place for data professionals and business users to discover, manage, and govern the data they own and can access across OneLake. With over 30M monthly active Power BI and Fabric users, it’s already the default source of data and insights for many business users. The OneLake catalog comes with two tabs, Explore and Govern, that can help all Fabric users discover and manage trusted data, as well as provide governance insights for data owners.

Instead of searching through a maze of databases or SharePoint sites, users can use the Explore tab and even narrow their search by domain, workspace, item type, endorsements, and more to find exactly what they need in seconds. You can then deep dive into a data item to see its description, owner, schema, lineage, and usage metrics. We’ve also integrated OneLake catalog everywhere your people work including Microsoft Teams, Microsoft Excel, Microsoft Copilot Studio, and 100s of other scenarios—bringing data access to the 350 million Microsoft 365 users.

In the Govern tab, data owners can get out of the box insights and recommended actions based on the curation and quality level of their data based on sensitivity label coverage, tagging, endorsements, data location, and more.

Check out the full demo of the OneLake catalog:

Share broadly with granular security and control

However, while broad access to data is critical for empowering the business, security leaders know that cyber-attacks are becoming more sophisticated, and the average cost of a single breach is nearing $10 million. Traditionally, the response is to lock down access to only trusted users, but our research tells us that 63% of data breaches stem from inadvertent, negligent or malicious insiders. The reality is people will try to work around lock down controls using tools like Excel which are harder to govern, less transparent, and harder to maintain.

That’s why we’ve designed OneLake security—an experience designed to help you share data across your organization without exposing sensitive information. With OneLake security, you can create roles to set permissions at the data item, folder, table, or even row/column level, enabling you to still share a data item while restricting access to any sensitive data your item may contain. These permissions are then automatically enforced across all analytics experiences, so whether a user is querying data through a Spark notebook, viewing it in a Power BI report, or exploring it through a Fabric data agent, OneLake’s security model ensures they see only what they’re permitted.

Check out this visual to see how OneLake security works:

This unified approach to security means users no longer have to maintain separate permissions across different engines. It also means the original data owners always maintain control over who can access the data source, even if the data is bypassed to another lakehouse or workspace owned by someone else. The end result is that data sharing can be done safely, knowing you have the fine-grained controls in place.

Check out this full overview video:

On top of this built-in security, you can also leverage the same security features from tools like Microsoft 365 with Purview Information Protection sensitivity labels and Purview Data Loss Prevention (DLP) policies. Technical and non-technical users alike can apply sensitivity labels to classify their data items, automatically restricting access based on the data item’s sensitivity even when the data exported to other tools like Microsoft Excel. DLP policies will also automatically detect when sensitive data is uploaded to unauthorized destinations, alerting users and offering guidance to mitigate risks.

In short, OneLake’s security model means you get the benefit of broad data accessibility and self-service analytics without sacrificing oversight and control. Together, these capabilities provide a unified, enterprise-grade framework for securing data, enabling responsible AI use, and ensuring compliance across the OneLake environment.

Building data-driven agents with curated data from OneLake

Creating custom AI experiences requires data—lots of it. Data is the foundation on which AI is built, and the simple fact is AI is only as good as the data it’s based on. For generative AI solutions to be as accurate as possible, they need to be built with clean data and in a semi-structured way. With your data in OneLake, you can use Fabric’s various workloads to make the data AI-ready. Fabric has tools for data integration and engineering, data warehousing, data science, real-time analytics, data modeling and visualization, and even has native, industry-specific and partner-created workloads to help you accelerate your data projects.

You can then directly connect your data to AI platforms like Azure AI Foundry to build and scale data-driven GenAI apps. We’ve built native integration between OneLake and Azure AI Foundry to make this as seamless as possible. The integration between Azure AI Foundry and OneLake is built on OneLake shortcuts, helping you work with your structured and unstructured data from OneLake in Azure AI Foundry without creating copies and adding more data sprawl. OneLake also directly integrates with Azure AI Search, which can store, index, and retrieve data, including vector embeddings, from your data sources including OneLake. 

Finally, you can ground your Azure AI Agent’s responses with data from Fabric using Fabric data agents to unlock powerful data analysis capabilities. Fabric data agents are AI-powered assistants that can learn, adapt, and deliver insights, allowing users to interact with the data through chat. With out-of-the-box authorization, this integration simplifies access to enterprise data in Fabric while maintaining robust security, ensuring proper access control and enterprise-grade protection.

Check out this full demo:

Conclusion: A unified data lake for your entire organization

Microsoft OneLake is more than just a new tool—it’s the strategic centerpiece of a data estate that can reshape how an organization harnesses data. By unifying data in one place and breaking down silos, it can become the single point for all your users to discover and explore your organization’s data organized into a logical data mesh. With shortcuts and mirroring in OneLake, you can unify all of your multi-cloud and on-premise sources and enable your people to work from a single copy of data—meaning fewer copies of data, better collaboration between your teams, and more streamlined analysis. By enabling collaboration on a single copy of data, it ensures every decision is based on the same facts, eliminating the version control and governance nightmares.

Organizations like Lumen, IFS, NTT Data, and the Chalhoub Group have all adopted Microsoft OneLake and Microsoft Fabric to unify ingestion, storage, and analytics in one platform. Using OneLake shortcuts, mirroring, Direct Lake mode, and more, Lumen—a leader in enterprise connectivity—cut 10,000 hours of manual effort, “We used to spend up to six hours a day copying data into SQL servers,” says Chad Hollingsworth, Cloud Architect at Lumen. “Now it’s all streamlined… OneLake allowed us to ingest once and use anywhere.” IFS, a leading provider of enterprise software, faced high costs and complexity from a fragmented data architecture. The company unified their data estate on Microsoft OneLake, increasing data access from 20% to more than 85%, cut costs, and accelerated insights, “the primary challenge we faced was the slow pace of development caused by managing separate extract, transform, load (ETL) processes and reporting environments,” said Ligy Terrance, Director of Data Analytics and Integration at IFS. “With Microsoft Fabric, we now have a unified platform that brings all these layers together… Having everything in one place has eliminated integration bottlenecks and made it much easier to deliver insights quickly and efficiently.”

For organizations trying to manage their ever-growing data estate, the implications are significant. OneLake’s approach translates to less data sprawl and lower total costs, less time spent by IT maintaining complex data pipelines and by users looking for data, and faster time to insights for data professionals. With its robust security and governance story, you can help ensure your data is secure while empowering your users with decision-changing data.

Learn more about how OneLake can work with your data estate

Join us for a series of blog posts over the next few months as we explore why Microsoft OneLake is the ideal data platform for the entire data estate. We’ll walk you through how OneLake integrates with each of these platforms, highlight top opportunities and use cases, and feature customers who’ve successfully transformed their existing solutions with OneLake. Check back to the Fabric blog site to find the latest blogs or bookmark this blog and we will update the list below with links to the relevant blogs.

We are planning the following topics:

1. OneLake and Microsoft Foundry: Build data-driven agents with curated data from OneLake
2. OneLake and Snowflake: Snowflake and Microsoft announce expansion of their partnership
3. OneLake catalog overview: OneLake catalog: The trusted catalog for organizations worldwide
4. OneLake and Azure Databases: Coming soon
5. OneLake and Azure Databricks: Microsoft and Databricks: Advancing Openness and Interoperability with OneLake
6. OneLake and Azure Data Factory: Coming soon
7. OneLake and Microsoft 365: Coming soon
8. OneLake and Microsoft Copilot Studio: Coming soon
9. OneLake and open-source solutions: Coming soon

The post OneLake: your foundation for an AI-ready data estate appeared first on Microsoft Fabric Blog.

A 2025 report from Gartner® highlighted the accelerating shift toward real-time data: “According to the Transforming Data With Intelligence (TDWI) survey, 38% of organizations plan to enable access to real-time data for driving operational use cases. In the 2024 Data Streaming Report, Confluent found that ‘51% of IT leaders cite data streaming as a top strategic priority for IT investments in 2024, compared to 44% in 2023.’ Additionally, 68% expect the use of data streaming technology to continue growing over the next two years.”^{1, 2}

Think fraud detection: every second counts. Or live customer monitoring, where spotting a behavior shift in real time can mean the difference between a lost sale and a loyal customer. In logistics, delays in anticipating and even preventing disruptions can cascade into missed deadlines, higher costs, and lost customers. These aren’t futuristic scenarios. They’re happening now, powered by real-time decision-making.

At the core of this shift is AI. By making decisions on the most up-to-date data, AI can detect anomalies, uncover patterns, trigger alerts, and continuously optimize workflows, as events unfold. No more waiting for yesterday’s reports to make tomorrow’s decisions.

Batch systems inherently operate on delay that doesn’t impact historical reporting, but isn’t sufficient for live operations. Streaming flips that model, delivering a continuous flow of insights when they matter most: now.

Henry Ford once said, “If I’d asked people what they wanted, they’d have said faster horses.” We don’t need faster batch jobs. We need a new paradigm. So instead of trying to speed up a process that isn’t designed for real-time, start where the action begins: at the moment data is born.

The pace of business has changed. Has your analytics kept up?

How is batch processing used today?

Enterprises today often use a centralized analytics team to handle batch processing. This involves extracting data from various sources, processing it through multiple stages in a “medallion architecture” (bronze, silver, gold), loading that data into a compute engine, and finally delivering it to end-users via tools like Power BI. This process is often slow and cumbersome, leading to delays in decision-making. Batch processing works when you have a very predictable set of data that always needs the same processing structure, but it suffers from:

• Delayed insights from reporting on stale data.
• A need for centralized control and governance.
• Pipeline failures affecting the whole batch.

In today’s dynamic world, our expectations and our customers’ expectations have increased to a more agile, adaptable framework. This is where real-time streaming comes into play.

What is real-time streaming?

Real-time streaming is a data processing paradigm that involves the continuous flow and analysis of data as it is generated. Unlike traditional batch processing methods that collect and process data at intervals, real-time streaming allows for instantaneous insights and responses, making it possible to act on information as events unfold.

This approach is increasingly vital in a range of applications, from fraud detection and live monitoring to dynamic decision-making in business processes. By leveraging real-time streaming solutions, organizations can enhance operational efficiency, improve responsiveness, and deliver more agile, data-driven experiences.

How do you know you need real-time streaming?

The shift to real-time often starts with a question. When organizations begin asking for faster insights, smarter automation, and more responsive systems, it’s a clear sign they’ve outgrown batch processing. Here are common signs: “I want to…”

• Respond to events in my business.
• Receive instant alerts when something changes.
• Monitor digital and physical assets continuously and in detail.
• Generate real-time reports and dashboards.
• Enable AI and machine learning to act in the moment.
• Scale systems without sacrificing performance.
• Build and deliver data products in real time.

If these needs resonate with you, your organization is ready to evolve. And your data infrastructure should, too.

What benefits does streaming data provide?

Streaming data enables faster and more responsive operations by delivering insights as events unfold. It eliminates the delays of batch processing and supports continuous awareness and action. With streaming data, businesses can:

• Detect and respond to changes instantly.
• Diagnose problems as they emerge and shorten the time-to-resolve.
• Power real-time dashboards and decision-making.
• Feed machine learning and generative AI with live, high-fidelity inputs.
• Monitor digital and physical assets continuously.
• Scale analytics without sacrificing performance.
• Deliver real-time data products to internal and external consumers.

This shift turns data into a live operational asset, driving immediate action, automation, and continuous improvement.

What is Real-Time Intelligence in Microsoft Fabric?

Real-Time Intelligence in Microsoft Fabric is built for the now. It delivers a powerful, unified SaaS platform for continuously ingesting, processing streaming data, training machine learning and AI models, and transforming raw signals into actions in real time. It bridges the gap between data and action. It’s not just about seeing what’s happening, it’s about responding as it happens.

Across industries, Real-Time Intelligence is already powering smarter, faster decision-making in thousands of organizations across a variety of industries:

Is Fabric Real-Time Intelligence cost-effective?

Microsoft Fabric Real-Time Intelligence is built for both performance and cost-efficiency. With a flexible, consumption-based pricing model, you only pay for what you use, whether it’s streaming ingestion, transformation, or event-driven processing, allowing you to start small and scale seamlessly. Unlike traditional batch systems, which often require heavy infrastructure and redundant data processing, it optimizes costs by processing only the most recent records in real time.

In many cases, it’s not just more responsive than batch. It’s more affordable. And compared to other streaming platforms, Real-Time Intelligence in Microsoft Fabric delivers powerful real-time capabilities at a lower total cost of ownership. Real-time insights don’t have to come at a premium.

The future is streaming, don’t let it pass you by

Real-time is no longer a luxury. It’s a competitive necessity. With Microsoft Fabric Real-Time Intelligence, you can harness streaming data with a streamlined, intuitive experience designed for scale, speed, and simplicity. It’s not about processing everything faster. It’s about processing the right data, as it happens, and turning it into action.

Say goodbye to outdated batch jobs, complex pipelines, and latency that holds your business back. With event-driven transformations and real-time ELT, you’re not just cleaning up data. You’re clearing the path to instant insight and smarter decisions.

The future of data is already in motion. Are you ready to move with it?

• Learn:
  • Use the docs
  • Complete the learning path
  • Get certified
• Get hands on:
  • Play the Kusto Detective agency
  • Complete the tutorial
• Engage:
  • Ask questions
  • Submit ideas
• Stay updated:
  • Read the blog
  • Follow us on LinkedIn
  • Watch us on YouTube

Check out the release plan.

¹Gartner, Emerging Tech: Revolutionize Your Products With Real-Time Data and AI, Kevin Quinn, David Pidsley, 31 January 2025.

²Gartner is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

The post Your business doesn’t wait, why should your analytics? appeared first on Microsoft Fabric Blog.

Leverage insights and analysis as a Fabric Data Engineer 

Microsoft Fabric unifies data tools, streamlining collection, storage, processing, and analysis of structured and unstructured data. Its AI capabilities enable advanced analytics, intelligent applications, and predictive insights, helping businesses stay competitive. 

Becoming a Fabric Data Engineer offers strong career prospects, as these professionals build data pipelines that transform raw data into valuable insights. Fabric simplifies complex workflows, enhancing business intelligence and AI applications. With demand for data engineers rising, expertise in Fabric provides a competitive edge, making it easier to implement advanced solutions and drive innovation in a data-driven world. 

Start your journey with the latest Azure Essentials Show episode 

From guided learning paths to interactive labs and detailed documentation, Microsoft Learn offers a structured approach to mastering the skills needed to excel as a Fabric Data Engineer. As the demand for skilled data engineers continues to rise, a recent installment of the Azure Essentials Show explores this market trend and introduces viewers to the wealth of learning resources we have available.

The show’s hosts walk through these resources, demonstrating how they cater to learners at different skill levels—from beginners just starting their data journey to experienced professionals looking to upskill in Microsoft Fabric. Here’s a rundown of what’s included: 

Elevate your Microsoft Fabric data engineering skills: Prepare for Exam DP-700 

Our official Plan on Microsoft Learn, Elevate your Microsoft Fabric data engineering skills: Prepare for Exam DP-700, is designed to prepare you for the DP-700 Fabric Data Engineer Associate certification exam. It offers a learning outcome and milestone-based approach that encourages continuous learning, and includes essential, curated Microsoft Learn modules. After completing it, you should be able to: 

• Describe the core features and capabilities of lakehouses in Microsoft Fabric. 
• Use Apache Spark DataFrames to analyze and transform data. 
• Use Real-Time Intelligence to ingest, query, and process streams of data. 
• Request your DP-700 exam voucher. 

Microsoft Fabric Data Engineer certification 

To validate your newfound expertise, passing our Microsoft Certified: Fabric Data Engineer Associate certification exam equips you with an industry-recognized credential. This certification attests to your proficiency in data loading patterns, data architectures, and orchestration processes within Microsoft Fabric. Earning this certification not only enhances your credibility but also opens up advanced career opportunities in the data engineering field.

Enhance your Microsoft Fabric analytics engineering skills: Prepare for Exam DP-600 

In another Plan on Microsoft Learn, Enhance your Microsoft Fabric analytics engineering skills: Prepare for Exam DP-600, you’ll learn about Fabric through the lens of data analytics. From mastering the basics to advanced data processing and management, this Plan covers everything you need to ace the DP-600 Certification exam. After completing the Plan, you should be able to: 

• Understand end-to-end analytics, including real-time intelligence. 
• Gain proficiency in using Apache Spark for ingesting data with Dataflows Gen2. 
• Learn how to create, manage, and optimize data warehouses. 

We’re also excited to offer a limited number of free Microsoft certification exam vouchers for the DP-600 exam! To submit your request form, click here for the full eligibility rules.

Implement operational databases in Microsoft Fabric

Excited to see what else you can discover about Fabric on Microsoft Learn? We also have a learning path called ‘Implement operational databases in Microsoft Fabric‘ that will guide you through the comprehensive process of creating and managing SQL databases within the Fabric environment. This course covers a range of important topics, including data modeling, query optimization, and performance tuning, all tailored to Fabric’s unique SQL capabilities. 

You’ll learn how to provision an SQL database, configure security settings, and perform essential database operations. Additionally, the course delves into advanced techniques for optimizing database performance and ensuring efficient data management. By the end of the learning path, you will have gained the expertise needed to effectively manage SQL databases within Microsoft Fabric, enabling you to leverage its powerful features for your organization’s data needs. 

Join the future of data analysis with Fabric 

Embarking on a career as a Fabric Data Engineer offers a pathway to be at the forefront of data innovation. With Microsoft Fabric’s unified platform and integrated AI capabilities, professionals in this role are equipped to design and manage cutting-edge data solutions that drive business success. To delve deeper into this exciting field, explore the featured episode of the Azure Essentials Show and consider pursuing the Fabric Data Engineer certification to validate and enhance your expertise. 

Microsoft Fabric

Experience the next generation in analytics.

Discover more

Don’t miss the FabCon Europe Super Early Bird discount 

And learning doesn’t stop there. Join us at FabCon Vienna this September to keep up the momentum!

FabCon Vienna brings to Austria the smashing success of last year’s Stockholm conference, with a wealth of cutting-edge learning opportunities from the world of data, analytics, and AI. Both Microsoft product team members, as well as community experts will be leading sessions. You’ll get endless chances all week to engage with the Fabric and data communities through thoughtful discussions, attendee mixers, and interactive experiences. The lowest early-bird pricing expires at the end of May, so register for the FabCon conference today. Use the code MSCUST to save an additional €200! 

The post Chart your course as a Microsoft Fabric Data Engineer with curated skilling and certifications appeared first on Microsoft Fabric Blog.

Microsoft Fabric

Bring your data together and empower everyone with valuable insights.

Get started with Fabric

Unlock the value of your data with Fabric

Fabric gives your teams the AI-powered tools they need for innovative data-informed decision-making and reporting projects. Fabric has many key features that help you get the most value from your organizational data.

With Fabric, you can:

• Govern and protect seamlessly
• Bring your institution’s data together
• Empower everyone with access to valuable insights
• Fuel your AI innovation

Take a Fabric training course

Fabric not only enables innovation but also saves money. A Forrester Total Economic Impact™ Study commissioned by Microsoft in 2024 highlights the cost savings and financial benefits of Fabric:

• 379% return on investment
• Payback in less than 6 months
• 25% increase in data engineering productivity
• 90% reduction in data engineering time related to searching, integrating, and debugging

Learn how Fabric can provide additional data insights and contribute to cost savings.

Govern and protect your data

The effectiveness of your AI relies on responsibly managing and securing a wide range of data, including educational records, financial information, and research data. Schools need a unified solution to govern and protect their entire data estate while unlocking its full potential. Fabric, seamlessly integrated with Microsoft Purview, provides comprehensive data governance and protection. It simplifies management, secures sensitive information with role-based access controls, and ensures compliance with privacy regulations. By unifying governance and security, institutions can protect personally identifiable information (PII), prevent data loss, and share insights securely and compliantly.

Play the video to learn how Fabric provides you with an end-to-end analytics platform.

Ensuring compliance is a pivotal step in becoming AI-ready. As you grow and expand your school’s AI innovation, it’s essential to design a strategy that strikes a balance between fueling paths to innovation and addressing pressing security priorities.

Auburn University turned to Microsoft and its comprehensive, flexible tools to develop approaches that would help them move forward and pivot as new technologies emerge. With tools like Microsoft Purview and Microsoft Sentinel providing security, Auburn developed more ways for people to explore AI’s possibilities safely.

Read more about how Auburn University is exploring new ways of using AI.

Additionally, Coquitlam School District faced challenges with data compliance and privacy, especially with unstructured data from teachers. To address these challenges, Coquitlam implemented Fabric and Microsoft Purview. These platforms transformed the district’s data management systems, turning unstructured data into actionable insights. Play this video to learn more about how Coquitlam School Districts achieved their goals around security and educational, operational, and organizational excellence.

Read Coquitlam’s full story and play the video to explore how this district is building a more secure infrastructure and enhancing data insights.

Bring your institution’s data together

Data management is most effective when it’s unified, governed, and compliant. As modern data platforms evolve with generative AI, the potential for data-driven decisions and operational optimizations grows. Fabric and OneLake unify your data and analytics to streamline transformation, deepen insights, and drive AI innovation. OneLake acts as a hub to build AI apps powered by your data, making it easy to virtualize and aggregate data from any source.

Fabric works with OneLake to centralize data, enabling seamless integration and improving data quality. Your institution can take your data from storage to Fabric and then to the Azure AI Foundry portal, where you can build custom AI apps.

Play the video to learn how Fabric and OneLake simplify data management and reduce data duplication.

As your institution introduces dynamic data tools like Fabric and OneLake, you’ll be able to transition to an end-user, self-service model, empowering staff members to access the data they need when they need it, and fostering a culture of data literacy.

The University of South Florida (USF) has accelerated data-driven decision-making by empowering its teams to access information and enriched business insights through a self-service approach. By preparing client technologists to do self-service analysis, USF has taken an important step on its ambitious digital transformation journey.

Read more about how USF is empowering employees to derive insights in minutes.

Empower everyone with access to valuable insights

Access to actionable insights is critical for driving meaningful change and improving decision-making across educational institutions. However, when data remains inaccessible to non-technical users, opportunities for innovation are often lost. Faculty and staff need intuitive tools to transform raw data into insights that support collaboration and institutional growth.

Streamline workloads Explore Microsoft 365 Education

Fabric addresses these challenges by democratizing data access. Seamlessly integrated into Microsoft 365, it allows staff to create reports with drag-and-drop tools and leverage AI to uncover trends and opportunities. Securely connected and certified datasets ensure trusted insights, while centralized databases enable leaders to drive growth and support strategic initiatives.

Politecnico di Milano exemplifies this transformation by leveraging Microsoft Graph Data Connect and Power BI to uncover objective workforce sentiment insights that surpass the limitations of traditional surveys. By accessing near real-time sentiment data, organizations can make quicker, more informed decisions, fostering collaboration and creating supportive work environments—all while maintaining data privacy. This innovative approach highlights how modern tools can revolutionize data accessibility and empower institutions to derive actionable insights at scale.

Read more about how Politecnico di Milano is redefining data-driven collaboration and innovation.

Enhance your AI innovation

Leveraging generative AI streamlines productivity improves quality, and increases value. Fabric, the data platform for the AI era, empowers your data professionals to unify data and build AI models on a single foundation. You can even use Copilot in Fabric to automate data insights, uncover trends, and enable faster interventions. This improves everything from academic outcomes to resource management, all within a transparent and trustworthy AI platform.

Using machine learning to generate actionable insights has enabled Broward College to respond to students’ needs more quickly. The technology allows the team to process data in minutes that would previously take days to complete—and to isolate complicating or potentially misleading factors, like the impact of the COVID-19 pandemic on student retention.

Read more about how Broward College uses Microsoft data tools to identify and respond to students’ needs.

Fabric is more than a tool—it’s a powerful platform to unlock new possibilities. By centralizing and securing your data, you can drive better outcomes for students, faculty, and your entire educational community.

Ready to start innovating? Begin your data innovation journey and achieve cost savings by signing up for a free 60-day Fabric trial.

Try Fabric for free

Explore the “Make your data AI-ready” training plan to master Microsoft Fabric. Learn to ingest, transform, and store data, and use Power BI to unlock insights for smarter decisions and better educational outcomes.

Start the Fabric training plan

The post Microsoft Fabric: The data platform for the AI era appeared first on Microsoft Fabric Blog.

With the maturation of cloud-native big data platforms and the exciting revolution in generative AI, the potential for data-driven decisions and operational optimizations has never been greater, raising the urgency of solving the longstanding problem of how to enable organizations to bring together estate-wide data for analytics.

The vision of open lakes for analytics

Unlocking data usage for the age of AI

Read the whitepaper

Optimizing processes by simplifying data

We believe that the emergence of open, updatable table formats presents us with a unique opportunity to solve this problem by standardizing these formats across all analytic engines, and by simplifying data replication. In fact, as an increasing number of engines adopt open data formats, we can minimize data replication by instead using references to data sources.

Further, as the value of data is recognized, we are seeing corresponding emphasis on right-use and increasing regulation. Thus, it is important that we be able to govern the entire data estate in a compliant manner, and in particular, evolve current best practices for aggregating estate-wide data to reflect the emerging world of cloud-native data lakes that bring together a diverse range of analytic capabilities, from exploratory tools, to AI models, to tools for serving data and rich business reports reliably, securely, and at scale.

Shaping the future of data analytics

This vision of the future of analytics is at the heart of OneLake design in Microsoft Fabric. We have striven to make it the “one place to bring all data for analytics”, making it easy to virtualize and aggregate data from all sources. Fabric itself then democratizes access to the wealth of insights that can be unlocked, thanks to a Microsoft 356-like simplicity in bringing analytic tools to bear on the data through intelligent software as a service, and by infusing AI copilot experiences to assist with complex tasks in-stride. The entire life cycle of analytics, from aggregating data to unlocking rich insights for appropriately authorized users, can be managed using the data governance capabilities of Fabric and the integrated estate-wide governance capabilities of Microsoft Purview.

Read the whitepaper to learn more!

The post Microsoft’s vision of an open data lake ecosystem: Open lakes, not walled gardens appeared first on Microsoft Fabric Blog.

Bring your data into the era of AI

Reshape how everyone accesses, manages, and acts on data with a single, AI-powered platform.

Start today

Take PricewaterhouseCoopers (PwC) for example, a leader in the professional services sector and a long-time technology innovator. PwC is applying generative AI to acquire, transform, and analyze data faster to better support its employees and provide better audit experiences for clients.

“We’re implementing Microsoft infrastructure to help future-proof NGA design, increasing the potential future adaptability of our assurance services and processes. Generative AI capabilities within the Azure OpenAI Service open up possibilities for us to enable natural language interfaces for enterprise data.” 

Winnie Cheng, Director of AI in Products and Technology at PwC

Connect your data with Fabric

PwC is not alone. Increasingly, organizations are turning to AI to transform their data cultures for better business outcomes. Traditionally, building this culture requires a few key ingredients:

1. Organizing your data into a logical data mesh to make it easier for users to discover, reuse, and enhance the best data available.

2. Creating a seamless analytics engine that can meet the demands of the business to uncover insights in real-time.

3. Infusing those insights into the applications your people use every day so they can make data-driven decisions.  

These steps are still vital, but now you can employ generative AI to accelerate the path to a data-rich culture by enhancing the productivity of your data teams and making analytics tools more accessible to everyone. In my webinar, Infusing AI into your Data Culture: A Guide for Data Leaders I walk through exactly how Microsoft can help you accomplish each step along this journey.

First, we’ll explore the blockers preventing users from discovering, accessing, and using data to innovate and make better decisions. I will also show you the promise of Microsoft Fabric’s single, SaaS, multi-cloud data lake, OneLake, designed to connect to any data across the organization and serve everyone who needs access to data in an organized, intuitive data hub. Your data teams can use the OneLake data hub to manage your data, endorse high-quality data to encourage use, and manage access. Users can easily find, explore, and use the data items that they have access to—from inside data tools like Fabric or even applications like Teams and Excel. For more on OneLake, read our e-book, Lakehouse Analytics with Microsoft Fabric and Azure Databricks. 

With your data accessible to those who need it, you also need to equip them with powerful analytics tools that can help them scale to the needs of the business. That’s where Microsoft Fabric further shines. With Fabric, data teams can use a single product with a unified experience and architecture that provides all the capabilities required for analysts to extract insights from data and present them to the business user. Each role in the analytics process has the tools they need, so data engineers, data scientists, data analysts, business users, and data stewards feel right at home. By delivering the experience as a SaaS platform, everything is automatically integrated and optimized, and users can sign up within seconds and unlock significant business value within minutes.  

With your data in a single place and your data teams empowered to uncover insights faster than ever, the next step is to get insights into the hands of everyone in your organization. I’ll show you how Power BI can infuse reports and insights into your apps like Microsoft 365, Dynamics 365, Power Platform, and even third-party apps like Salesforce and SAP.  

And now, as we enter a future built on AI, I’ll walk you through three key ways generative AI can help foster a more data-rich culture: 

1. Take advantage of out-of-the-box experiences like Copilot in Fabric which helps you accelerate the productivity of your data teams.  
2. Employ powerful AI models right from Fabric to draw deeper insights from your data. 
3. Create custom AI experiences, grounded on your data, with native integration between Microsoft Fabric and Azure AI Studio.

See these capabilities in action 

If you’re interested in learning more, I’d encourage you to join my webinar on Infusing AI Into Your Data Culture: A Guide for Data Leaders. I’d also encourage you to try Microsoft Fabric and Azure AI Studio out for yourself and learn more about how to adopt and foster a data-driven culture by reading the Microsoft Fabric adoption roadmap on data culture.

The post Foster a more data-driven culture with generative AI in Microsoft Fabric appeared first on Microsoft Fabric Blog.

In today’s rapidly evolving data and AI landscape, the demand for comprehensive event and streaming analytics solutions has never been more critical. Over the past few years, Microsoft has dedicated itself to investing in this area and addressing the needs of its customers by offering seamless and powerful options for stream processing. This includes Microsoft Fabric Real-Time Analytics, a robust solution built upon the scalable, fault-tolerant foundations of Azure Streaming Data Platform services. 

We’re excited to announce that our investments are paying off. Microsoft has been recognized as a Leader in The Forrester Wave™: Streaming Data Platforms, Q4 2023—a distinction based on Forrester’s evaluation of the advanced capabilities of Azure Event Hubs and Azure Stream Analytics services.   

Microsoft not only secured the highest score among all vendors in the “current offering” category, but was also given the top score possible of 5.0 across 13 distinct criteria. The Forrester report acknowledges Microsoft’s strengths in streaming analytics, low latency, fault tolerance, and developer tools. You can read the full The Forrester Wave™: Streaming Data Platforms, Q4 2023 to learn more about Microsoft’s position as a leader in the evaluation.   

Why is Stream processing important?   

Stream processing has emerged as a crucial technology, revolutionizing the way data is collected, analyzed, and insight-based decisions are made, all in real-time. But the benefits of stream processing extend beyond just speed. It gives organizations a holistic 360-degree view of real-time and batch data empowering them to detect anomalies, identify patterns, and extract valuable insights from the continuous influx of data. This not only enhances decision-making processes but also enables businesses to deliver personalized and responsive experiences to their customers. With reduced latency and immediate feedback loops, stream processing fosters a more agile and adaptive approach to data-driven decision-making, ultimately contributing to increased efficiency, innovation, and a critical edge in today’s competitive market.  

However, stream processing at a cloud scale can be challenging for businesses, both large and small. Integration complexities with existing services, the need for efficient resource scaling, ensuring reliability and fault tolerance, and addressing security concerns pose significant hurdles. Striking a balance between seamless integration, scalable infrastructure, and robust security measures is crucial for successful cloud-based stream processing implementations.   

Why do customers love Azure Streaming Data Platform?  

Microsoft Azure addresses these challenges with one powerful solution on two products—Azure Event Hubs and Azure Stream Analytics. Azure Event Hubs provides a scalable and open event ingestion service, simplifying the integration of stream processing frameworks. Complementing this, Azure Stream Analytics enables users to build and deploy complex stream processing queries. Together, these services enable businesses to ingest, process, and analyze massive amounts of data in real-time. With built-in security, reliability features, and developer tools, Microsoft Azure services ensure data protection, business continuity, and productivity—at a flexible price point that makes stream processing at scale affordable for all Azure customers.    

• Ingestion and stream analytics: Azure Event Hubs has native, on-by-default support for Open standards such as Apache Kafka and AMQP, enabling customers to ingest data from a wide variety of data sources. Meanwhile, Azure Stream Analytics supports output data into multiple services including Microsoft Power BI, Azure Functions, Azure SQL, and Azure Data Lake Storage. The support for Delta Lake (Delta Parquet) enables customers to persist the output of the stream analytics process in a way that can then be consumed by popular analytics services like Fabric, Azure Synapse, and Azure Databricks. By facilitating seamless integration between best-in-class tools and frameworks, Azure Streaming Data Platform services ensure that data flows smoothly from ingestion through to analytics, optimizing the value Azure customers can derive from their data assets.  

• High scale (latency and throughput): Azure Streaming Data Platform services are the backbone for thousands of leading enterprises that have come to depend upon the proven performance at planet scale. Azure Event Hubs has consistently exceeded the OpenMessaging Benchmark standards demonstrating end-to-end latency of under 10 milliseconds. Additionally, Azure Streaming Analytics, built upon multiple patented optimizations, supports data processing at a throughput of several GBs per second. These two services are handling over 10 trillion requests and more than 13 PB data ingested per day. This combination of low latency and high throughput equips businesses with the capability to manage, process, and analyze vast volumes of data at a very high velocity. This enables businesses to gain a significant advantage by making quicker, more informed decisions, and staying ahead of their competitors in today’s fast-paced market.   

• Fault tolerance and reliability: Built upon the robust, fault-tolerant foundation of Microsoft Azure and features such as availability zones, the Azure Streaming Data Platform is engineered for resilience. This ensures an unparalleled level of reliability and fault tolerance, providing our customers with peace of mind through a financially backed 99.99% uptime guarantee. Thousands of customers across various industries rely on our Streaming Data Platform services for their mission-critical applications, trusting in our platform’s consistent performance, reliability and the assurance of operational continuity, even in the face of unexpected challenges.   

• Security and privacy: Security is paramount in the digital age, and Azure takes this seriously. Both Azure Event Hubs and Azure Stream Analytics come fortified with robust security capabilities. Features such Microsoft Entra-based modern authentication, full compute isolation with dedicated clusters, native VNET integration, and end-to-end encryption using customer managed keys (CMK) ensures that businesses can navigate the data landscape with confidence, knowing that their valuable information is not just processed but safeguarded with the highest standards of security and privacy.  

• Developer productivity and tools: Azure’s commitment to high productivity is reflected in the suite of developer tools like Visual Studio Code, user-friendly web interfaces, and the low-code/no-code experiences of both Azure Event Hubs and Stream Analytics. Features such as “capture data” and “process data” are designed to simplify routine tasks, enabling data engineers to quickly accomplish their objectives without the need to navigate through complex configurations, service integrations, or job scheduling and monitoring. This focus on streamlining the development experience not only boosts efficiency but also accelerates the deployment of data-driven solutions, enabling teams to focus on innovation rather than administrative overheads.   

• Streaming in the age of AI: The integration of machine learning features amplifies the analytical capabilities of Azure’s streaming solutions in this age of AI including anomaly and fraud detection. The ability to call out to real-time scoring APIs and Azure Cognitive APIs from Azure Stream Analytics jobs are just the start.  

• Pricing flexibility: Achieving business efficiency, customer satisfaction, and user productivity shouldn’t come at an exorbitant cost. To that end, Azure Event Hubs and Azure Stream Analytics offer a variety of flexible pricing options tailored to meet the needs of businesses and use cases of all sizes. Whether you’re a small startup or a large enterprise, our pricing models are designed to provide cost-effective access to advanced stream processing capabilities. This approach ensures that businesses can leverage the power of real-time data analytics without compromising on financial objectives, ultimately driving better business outcomes, enhancing customer satisfaction, and promoting overall productivity.   

• Globally available: Azure Event Hubs and Azure Stream Analytics services are available in over 60 Azure regions around the globe. This number keeps growing to meet more customer demand. So, whether Azure customers need high-speed network access or have data sovereignty requirements, Stream Processing services are always in a region near them.  

If you are looking for a cloud-based streaming data platform that offers reliability, openness, performance, and affordability, look no further than Microsoft Azure. Azure Event Hubs and Azure Stream Analytics are the leading solutions in the market, enabling you to harness the power of stream processing for your business needs with ease and promoting a culture of innovation without unnecessary complexity. And we are not done! With Microsoft Fabric Real-Time Analytics and Data Activator, we have taken the next steps towards an even more accessible and seamless Software as a Service (SaaS) experience for you.  

The road ahead with Fabric Real-Time Analytics  

Microsoft Fabric Real-Time Analytics offers a powerful suite of features for handling real-time data, all seamlessly integrated under a consistent user experience, security model, and capacity model. Event streams enables ingestion and processing of streaming data from a wide variety of sources including Kafka, Azure, and into Fabric Lakehouse and Kusto Query Language (KQL) databases, enabling efficient analytics, real-time dashboarding, anomaly detection, and monitoring. Data Activator empowers users to define actionable patterns within their data, from simple thresholds to complex trends, driving informed decisions and alerts. All together, Fabric Real-Time Analytics and Data Activator provide a low-code/no-code experience for high-volume, high-granularity data within the unified AI-power analytics platform of Microsoft Fabric.   

Discover solutions

Learn more streaming data platforms on Azure and Microsoft Fabric:

• Microsoft Azure Event Hubs
• Microsoft Azure Stream Analytics
• Real-Time Analytics in Fabric

Real-Time Analytics in Fabric

Reduce complexity and simplify data integration

Read the documentation

The post Microsoft is recognized as a Leader in The Forrester Wave™: Streaming Data Platforms appeared first on Microsoft Fabric Blog.

These are some of the questions that we explore in Insights Tomorrow, a podcast for data enthusiasts of all levels. Whether you are a student, a professional, a hobbyist, or just curious about data, this podcast is for you. In each episode, we interview experts and practitioners from different fields and domains, who share their insights and experiences with data. We also discuss the latest trends and developments in data science, data journalism, data visualization, data ethics, and more. 

Our goal is to help you learn something new, get inspired, and have fun with data. We believe that data matters, and that everyone can benefit from learning how to use data effectively. So, join us as we dive into the world of data and discover how data can make a difference in our lives and society. 

Insights Tomorrow podcast

Unlocking value from data

Listen now

About the host

Insights Tomorrow is hosted by Patrick LeBlanc, Principal Program Manager at Microsoft and contributing partner to Guy in a Cube. Along with his over 15 years of experience in IT, he holds a Master of Science degree from Louisiana State University. He is the author and co-author of five SQL Server books. Before joining Microsoft, he was awarded the Microsoft MVP award for his contributions to the community. Patrick is a regular speaker at many SQL Server conferences and community events. 

How to listen and subscribe 

You can find Insights Tomorrow on our website, where you can listen to the episodes online or you can also subscribe to Insights Tomorrow on your favorite podcast app, such as Spotify, Apple Podcasts, or Amazon Music. 

Why should you listen and subscribe 

• You will learn from experts and practitioners who have real-world experience and knowledge with data. 
• You will discover new tools, techniques, methods, and resources that can help you improve your data skills and projects. 
• You will get inspired by the stories and examples of how data can be used for good, for innovation, for creativity, and for social change. 
• You will have fun and enjoy the conversations and discussions that we have with our guests and hosts. 
• You will become part of a community of data enthusiasts who share your passion and curiosity for data. 

So, what are you waiting for? Start listening and subscribe to Insights Tomorrow today and join us on our journey to explore the world of data. Here are episodes that you can tune into from our respected guests on the podcast and stay tuned for more episodes soon! 

Episodes

Episode #1: Reframing Data Strategy Alignment 

Organizational alignment on a data strategy is essential to realizing the transformative impact of applying an organization’s data to its fullest potential. This is easier said than done, despite there being a general alignment amongst an organization’s leaders on the transformative opportunities to apply their data. Why is it hard for an organization to align a data strategy? What is the top-line considerations for an organization’s leadership to avoid or break out of the deadlock states that hinder the acceleration of data value creation? What is the breakthrough path for the Data Strategy Alignment Conundrum? 

Guest: Karthik Ravindran, General Manager of Enterprise Data at Microsoft. 

Episode #2: Demystifying Data Modernization Patterns 

Data modernization refers to the process of upgrading and transforming data systems, infrastructure, and processes to meet the demands of modern data-driven organizations. It involves the adoption of new technologies and techniques to increase data quality, speed, scalability, and agility. To help organizations navigate this complex process, several data modernization patterns have emerged that provide a framework for modernizing data systems. 

Guest: Jeeva AKR, Leads the Cloud Scale Analytics go-to-market for Microsoft. 

Episode #3: What’s Governance Got to Do with It? 

Every data and analytics leader knows a simple but critical fact: your data is only as good as your governance. It’s essential to have data stewards and well-defined guidelines to keep your data clean, secure, organized, and compliant. But what does good governance look like in a world where data lives everywhere and is constantly changing? 

Guests: Erik Zwiefel, Chief Data and Analytics Officer for the Americas, Cumarran Kaliyaperumal, Chief Data and AI Officer for APAC. 

Epsiode #4: The Health of Data 

Having real-time access to secure, accurate data is critical in the healthcare industry. From storage and data integration to enabling governance across all of the systems that rely on sensitive patient information, every aspect of data management must be carefully considered when implementing a cloud strategy. Advancements in technology have made it easier than ever for healthcare professionals to access up-to-date information and gain new insights that can improve patient care. 

Guest: Anders Reinhardt, Senior Director of Business Intelligence and Global IT at Coloplast. 

Epsiode #5: The Blooming of AI Spring 

Artificial Intelligence, or AI, is a term that’s synonymous with the world of data. From data inputs that have driven the growth of AI, to the modern applications that can be applied to data models to accelerate time to insights, AI is at the forefront of innovation. But that hasn’t always been the case. Today we’re in the midst of a renewed “AI Spring” where we’re seeing a resurgence in development and new possibilities we never thought imaginable. 

Guest: Buck Woody, Applied Data Scientist on the Azure Data Services team at Microsoft. 

Episode #6: Microsoft’s Next Evolution 

From Online Analytical Processing (OLAP) to Vertipaq to Power BI, Microsoft has a rich history of innovation and evolution in business intelligence. As data becomes an ever-increasing priority for organizations around the globe, Microsoft is now focused on the future with the launch of Microsoft Fabric, a unified software as a service (SaaS) solution which integrates all your data in one place. Fabric makes data management easier and more accessible for every user who works with data. 

Guest: Amir Netz, CTO of Microsoft’s Intelligence Platform, including Power BI, Synapse, and more. 

Episode #7: What Happened to Data Marts 

Accessing data faster, more easily, and in a format of their choice is an increasing priority for business users. In the new Microsoft Fabric unified ecosystem, data warehousing, data lakehouse, and data marts coexist to enable users to choose how they analyze and work with data at scale. Priya Sathy shares insights into the future of data marts, the role data warehouses play, and what you can expect from Microsoft Fabric in the coming years. 

Guest: Priya Sathy, Leads Microsoft’s Azure Synapse SQL and Synapse Data Warehouse in Microsoft Fabric.

Episode #8: The Changing Faces of Data and Analytics 

Through actively incorporating the feedback of internal field sellers, engineers, and customers, Microsoft has been able to make huge strides in the development and success of the Power BI solution. Now with the introduction of Microsoft Fabric, another exciting shift is happening in the world of analytics. In this episode of Insights Tomorrow, Arun Ulag discusses his journey from being a field seller, through evolutions in Power BI, to the recent launch of the unified analytics solution, Microsoft Fabric. Arun also shares his insight and predictions for what lies ahead in this ever-evolving data and analytics landscape. 

Guest: Arun Ulag, Corporate Vice President of Azure Data. 

Epsiode #9: Patrick Takes the Hot Seat 

The data landscape is changing constantly, and as an expert in the space, our host Patrick LeBlanc is helping to document these changes and keep global data leaders updated on the latest developments and technologies. In this special episode of Insights Tomorrow, Product Marketing Manager Swetha Mannepalli interviews the interviewer, asking Patrick about his favorite moments from the podcast series and his predictions for what’s coming in data and AI. 

Guest: Swetha Mannepalli, Senior Product Marketing Manager. 

Episode #10: Finding Balance in Progress 

In today’s episode of Insights Tomorrow, Patrick LeBlanc and guest Kim Manis discuss the importance of balance and prioritization in both personal and professional lives. As the Director of Product, Microsoft Fabric & Power BI, Kim shares her experience in leading global teams, inspiring interns, driving success for innovative solutions, and saving space for the things she loves. 

Guest: Kim Manis, Microsoft’s Partner Director of Product Management, Azure Synapse Analytics, and Power BI. 

Learn more about the data landscape and Microsoft Fabric

• Check out the Insights Tomorrow podcast. 
• Explore more about Microsoft Fabric. 

The post Insights Tomorrow: A podcast for data enthusiasts  appeared first on Microsoft Fabric Blog.