Speed up Oracle to SQL Server Migrations with AI and Copilot | Data Exposed This episode provides an overview of Copilot in SSMA for Oracle, showcasing how AI improves code conversion accuracy, reduces manual effort, and guides users through complex migration blockers. It also walks through available authentication methods and offers a glimpse into future roadmap investments. ✅Chapters: 0:00 Introduction 1:20 Why Copilot in Migrations 2:30 Demo 6:55 What's next ✅ Resources: What is Microsoft Copilot in SSMA for Oracle?: https://learn.microsoft.com/en-us/sql/ssma/oracle/copilot-in-ssma-overview?view=sql-server-ver17 📌 Let's connect: Twitter - Anna Hoffman, https://twitter.com/AnalyticAnna Twitter - AzureSQL, https://aka.ms/azuresqltw 🔴 Watch even more Data Exposed episodes: https://aka.ms/dataexposedyt 🔔 Subscribe to our channels for even more SQL tips: Microsoft Azure SQL: https://aka.ms/msazuresqlyt Microsoft SQL Server: https://aka.ms/mssqlserveryt Microsoft Developer: https://aka.ms/microsoftdeveloperyt #AzureSQL #SQL #LearnSQL

Channel9 Speed up Oracle to SQL Server Migrations with AI and Copilot | Data Exposed: This episode provides an overview of Copilot in SSMA for Oracle, showcasing how AI improves code conversion accuracy, reduces manual effort, and guides users through complex… #Oracle #SQLServer #DataExposed

DiskANN: An overview of vector indexing in Azure SQL and Fabric SQL | Data Exposed At Ignite 2025 we announced the support for vector indexing in the SQL Server engine, using the DiskANN algorithm that is used all across Azure Databases. In this episode, we'll see how to create and use the vector index, the current limitation existing in Public Preview, and some cool solutions that can be created thanks to the fact that AI, Vectors and Data are all in one place: the MSSQL engine. ✅ Chapters: 0:00 Introduction 0:56 Demo 9:36 Demo 14:35 Resources 15:25 Samples ✅Resources: https://aka.ms/sqlai https://ai.awesome.azuresql.dev/ 📌 Let's connect: Twitter - Anna Hoffman, https://twitter.com/AnalyticAnna Twitter - AzureSQL, https://aka.ms/azuresqltw 🔴 Watch even more Data Exposed episodes: https://aka.ms/dataexposedyt 🔔 Subscribe to our channels for even more SQL tips: Microsoft Azure SQL: https://aka.ms/msazuresqlyt Microsoft SQL Server: https://aka.ms/mssqlserveryt Microsoft Developer: https://aka.ms/microsoftdeveloperyt #AzureSQL #SQL #LearnSQL

Channel9 DiskANN: An overview of vector indexing in Azure SQL and Fabric SQL | Data Exposed: At Ignite 2025 we announced the support for vector indexing in the SQL Server engine, using the DiskANN algorithm that is used all across Azure Databases. In this episode,… #AzureSQL #SQLServer #DataExposed

What's new in Fabric Data Warehousing - 2025 roundup | Data Exposed Let's dive into the major updates and innovations that came to Microsoft Fabric Data Warehousing in 2025, including features like Data Clustering, IDENTITY columns, MERGE, Migration Assistant, Security Features, and more! ✅ Chapters: 0:00 Introduction 2:38 Fabric Data Warehouse in 2025 3:49 Data Clustering 4:50 IDENTITY columns 5:54 MERGE 6:54 Migration Assistant 8:05 Security Features 9:45 What's next ✅ Resources: Fabric Roadmap, Administration, Governance and Security: http://aka.ms/fabricroadmap 📌 Let's connect: Twitter - Anna Hoffman, https://twitter.com/AnalyticAnna Twitter - AzureSQL, https://aka.ms/azuresqltw 🔴 Watch even more Data Exposed episodes: https://aka.ms/dataexposedyt 🔔 Subscribe to our channels for even more SQL tips: Microsoft Azure SQL: https://aka.ms/msazuresqlyt Microsoft SQL Server: https://aka.ms/mssqlserveryt Microsoft Developer: https://aka.ms/microsoftdeveloperyt #AzureSQL #SQL #LearnSQL

Channel9 What's new in Fabric Data Warehousing - 2025 roundup | Data Exposed: Let's dive into the major updates and innovations that came to Microsoft Fabric Data Warehousing in 2025, including features like Data Clustering, IDENTITY columns, MERGE,… #DataWarehousing #MicrosoftFabric #DataExposed

Implementing Vector Search in Your Application with SQL Server 2025 | Data Exposed: MVP Edition Going a level deeper than a basic semantic search talk, we’ll explore semantic search, how to implement it in your app, and how to ingest data at scale to support your application’s AI needs. ✅ Chapters: 0:00 Introduction 3:50 Demo ✅ Resources: https://learn.microsoft.com/en-us/sql/t-sql/functions/vector-search-transact-sql?view=sql-server-ver17 https://learn.microsoft.com/en-us/sql/sql-server/ai/vectors?view=sql-server-ver17 https://github.com/Azure-Samples/azure-sql-db-vector-search About Joseph D'Antoni: Joseph D'Antoni is an Principal Consultant at Denny Cherry and Associates Consulting. He is recognized as a VMWare vExpert and a Microsoft Data Platform MVP, and has over 20 years of experience working in both Fortune 500 and smaller firms. He has worked extensively on database platforms and cloud technologies and has specific expertise in performance tuning, infrastructure, and disaster recovery. About MVPs: Microsoft Most Valuable Professionals, or MVPs, are technology experts who passionately share their knowledge with the community. They are always on the "bleeding edge" and have an unstoppable urge to get their hands on new, exciting technologies. They have very deep knowledge of Microsoft products and services, while also being able to bring together diverse platforms, products and solutions, to solve real world problems. MVPs make up a global community of over 4,000 technical experts and community leaders across 90 countries/regions and are driven by their passion, community spirit, and quest for knowledge. Above all and in addition to their amazing technical abilities, MVPs are always willing to help others - that's what sets them apart. Learn more: https://aka.ms/mvpprogram 📌 Let's connect: Twitter: Anna Hoffman, https://twitter.com/AnalyticAnna Twitter: AzureSQL, https://aka.ms/azuresqltw 🔴 To watch other MVP Edition episodes, see our playlist: https://aka.ms/dataexposedmvps To check out even more Data Exposed episodes, see our playlist: https://aka.ms/dataexposedyt 🔔 Subscribe to our channels for even more SQL tips: Microsoft Azure SQL: https://aka.ms/msazuresqlyt Microsoft SQL Server: https://aka.ms/mssqlserveryt Microsoft Developer: https://aka.ms/microsoftdeveloperyt #AzureSQL #SQLServer

Channel9 Implementing Vector Search in Your Application with SQL Server 2025 | Data Exposed: MVP Edition: Going a level deeper than a basic semantic search talk, we’ll explore semantic search, how to implement it in your app, and how to ingest data at scale to… #VectorSearch #SQLServer #DataExposed

FinWise Data Breach Exposes Insider Threats, Highlights Need for Strong Encryption and Key Management  The 2024 FinWise data breach underscores the rising risk of insider threats within financial institutions. Unlike cyberattacks initiated by external hackers, this breach resulted from unauthorized access by a former employee who retained system credentials after leaving the company. On May 31, 2024, the ex-employee accessed FinWise Bank’s internal systems and leaked personal information of approximately 689,000 customers of American First Finance (AFF). The breach went unnoticed for more than a year, until FinWise discovered it on June 18, 2025. This prolonged exposure period raises serious concerns about the bank’s internal monitoring and incident detection capabilities.  Legal complaints against FinWise allege that the compromised data was inadequately encrypted, intensifying public scrutiny and regulatory pressure. Security experts emphasize that effective information protection involves more than encrypting financial data; it requires continuous monitoring, abnormal access detection, and secure key management. FinWise’s alleged failure to deploy these essential safeguards has led to lawsuits and reputational damage. While the bank has yet to disclose details about its encryption protocols, experts agree that encryption alone cannot protect data without proper implementation and access controls.  The incident highlights how encryption serves as a final layer of defense, but its effectiveness depends on complementary systems like key management and access control. Proper encryption management could have minimized the risk of data exposure, even after unauthorized access. In this context, Penta Security’s D.AMO encryption platform has gained renewed attention as an all-in-one defense solution against such vulnerabilities.  D.AMO, South Korea’s first packaged encryption solution launched in 2004, integrates encryption, granular access control, and an independent key management system (KMS). Trusted by over 10,000 clients across the finance, public, and enterprise sectors, D.AMO ensures data confidentiality while maintaining operational efficiency. It supports multiple encryption methods and selective column-level encryption, reducing system slowdown without compromising data protection.  The platform’s key management system, D.AMO KMS, operates as a dedicated hardware appliance that keeps encryption keys separate from the data they protect. By dividing the roles of database and security administrators, D.AMO prevents unauthorized individuals—including insiders—from accessing both encrypted data and the keys simultaneously. Even if an attacker breaches the database, the absence of decryption keys renders the stolen data unusable.  Additionally, D.AMO Control Center provides centralized management across an organization’s encryption systems. It allows administrators to monitor logs, enforce role-based access controls, and manage permissions to reduce insider misuse. This centralized visibility helps institutions detect unusual behavior early and maintain compliance with international data security regulations such as PCI-DSS, GDPR, and CCPA.  The FinWise breach serves as a cautionary tale about the consequences of weak encryption governance and insufficient access monitoring. It demonstrates that robust data protection requires a proactive, multi-layered approach integrating encryption, key management, and centralized oversight. Penta Security’s D.AMO platform embodies this strategy, offering institutions a unified solution to mitigate both external and insider threats. For organizations managing sensitive customer information, implementing comprehensive encryption frameworks is no longer optional—it is essential for preserving trust, compliance, and long-term security resilience.

FinWise Data Breach Exposes Insider Threats, Highlights Need for Strong Encryption and Key Management #Cyberattacks #DataBreach #Dataexposed

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Channel9 SQL database in Fabric - What's new and improved in public preview? | Data Exposed #SQL #Database #DataExposed

- YouTube Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.

Channel9 Creating smart prompts for Azure SQL Copilot to expose the pain | Data Exposed: MVP Edition #AzureSQL #SQLCopilot #DataExposed

Channel9 Get Data into Fabric Eventhouse | Data Exposed #DataExposed #Eventhouse #YouTube

Channel9 SQL Server 2025: Mirroring for SQL Server in Fabric | Data Exposed #SQLServer #DataExposed #Mirroring

Channel9 SQL Server 2025: Mirroring for SQL Server in Fabric | Data Exposed #SQLServer #DataExposed #DatabaseManagement

SQL Server 2025: Secure by Default | Data Exposed YouTube video by Microsoft Developer

Last week, Anna Hoffman, Pratim Dasgupta, and I dropped a fresh episode of Data Exposed — and it’s all about what’s new in #SQLServer2025 security. www.youtube.com/watch?v=t03T... #DataExposed #SQLServer #Security #MicrosoftEntra #DataSecurity

Channel9 Vector Support Public Preview in Azure SQL Database & Managed Instance | Data Exposed #AzureSQL #DataExposed #ManagedInstance

Channel9 Azure SQL Database Hyperscale: Elevating Performance with Continuous Priming | Data Exposed #AzureSQL #Hyperscale #DatabasePerformance #ContinuousPriming #DataExposed

Channel9 Perf Dashboard in Fabric SQL DB | Data Exposed #PerfDashboard #FabricSQL #DataExposed #YouTube #DataAnalytics

Channel9 Build Gen AI applications with LangChain and SQL | Data Exposed #GenAI #LangChain #SQL #DataExposed #AIApplications

Channel9 SQL Databases in Fabric – is it different from Azure SQL? | Data Exposed: MVP Edition #SQL #Databases #AzureSQL #DataExposed #YouTube

Channel9 How to use Automatic backups in SQL database in Microsoft Fabric | Data Exposed #SQL #Database #MicrosoftFabric #DataExposed #YouTubeTutorial

5 things to know about SQL and AI | Data Exposed YouTube video by Microsoft Developer

Hey, it looks like a new episode of #DataExposed just dropped! The title says it all: "5 things to know about SQL and AI". Check it out to have a quick recap of all the fantastic features we've been working to seamlessly integrate AI with #AzureSQL! www.youtube.com/watch?v=oZk2...

My picks this week were the PHENOMINAL @HeidiHasting & @hamish-watson.bsky.social & Hedi Hastings and another DYNAMIC DUO Mr. Bob Ward hosting Anna Hoffman on his show #DataExposed 😉

Check out their GREAT content in the description of the video!

Announcing SQL database in Microsoft Fabric public preview | Data Exposed YouTube video by Microsoft Developer

Last week, Marisa proudly kicked off a Microsoft Fabric Databases video series with #DataExposed & Anna Hoffman! New episodes over the next few months will keep you informed about the latest advancements
Check it out youtu.be/uYBIBZDHAeg
#MicrosoftFabric #AzureSQL #FabricDatabases #SQLinFabric

Watching: Native Windows principals for #SQL Managed Instance | #DataExposed #AzureData #AzureSQLMI https://buff.ly/3M5rLEG

Watching: #Azure #SQL free database: Azure Data Studio, #PowerApps, #GitHub copilot, Power BI, and Generative AI #AzureData #DataExposed #PowerBI #GenAI https://buff.ly/4dv1DPv

There is a shattered glass globe with clusters of telephone numbers and lines in a digital art style, creating sharp shadows on the ground.

Data breach, shattered trust,
Clusters of numbers, shadows cast. #DataExposed #ShadowedTruth #ShatteredGlobe #CallRecords #DataBreachConsequences #Geolocation

3 tools to help you move to #Azure with @SQLMelody
#DataPlatformMVP #DataExposed #AzureDataCommunity #GreatPokerFace
 
https://youtu.be/RNyNqK0gERM

No @AnalyticAnna - apparently I cannot introduce myself! 😂🤣😂
#DataExposed https://t.co/KskTqo0ElE

Thanks @AdiPolak for taking the time today to join me to record a #DataExposed episode! It was great talking to you. Stay tuned everyone, the episode will air soon!

#SQLServer #bigdataclusters data pools help optimize query performance when reaching out to multiple sources. . In this episode of #DataExposed we dive into when and how to use them. https://t.co/lMTcSbkA5N #sqlfamily #mssql #sqlserver2019

Compute pools are a really powerful feature of #SQLServer #bigdataclusters to offload distributed query processing. In this episode of #DataExposed we dive into when and how to use them. https://t.co/B3GYAZwdXx #sqlfamily #mssql #sqlserver2019

I met with @nelliegson to talk about #security for #SQLServer #bigdataclusters? See what we discussed in this episode of #DataExposed. channel9.msdn.com/Shows/Data-Exposed/Overv... #sqlfamily #mssql #sqlserver2019

Want to learn more about configuring #SQLServer #bigdataclusters? I asked @MihaelaBlendea a couple of questions about it in this episode of #DataExposed. channel9.msdn.com/Shows/Data-Exposed/Big-D... #sqlfamily #mssql #sqlserver2019