Systems | Development | Analytics | API | Testing

Databricks helps companies process large-scale data, and Databricks data masking ensures high-quality, compliant data. If your organization relies on data for AI/ML or analytics, it’s essential to ensure you are implementing a robust, compliant data masking strategy. Let’s explore how data masking works natively in Databricks. Then, we’ll go over challenges teams might run into in using native masking capabilities.

MISRA C:2025 has just been published! What does this mean for organizations that rely on MISRA guidance for developing safety-critical systems? In this blog, we give an overview of the new release and what it means for your team.

Microsoft Fabric combines data engineering, warehousing, real-time analytics, and BI into a single environment to help organizations streamline data workflows and derive insights from large, diverse datasets. For teams leveraging Fabric, data masking is an essential method for safeguarding sensitive data, ensuring compliance, and maintaining data quality throughout analytics pipelines.

Software has become a core component of modern vehicles, so much that software defined vehicles (SDVs) are transforming the automotive market, bringing key features to the software rather than the hardware of the vehicle. But developing high-quality code for software defined vehicle architecture is challenging.

Last week, industry leaders gathered at the Game Technology Summit during GDC 2025 to explore emerging trends and challenges in game development. The panel discussion, moderated by Jase Lindgren (Sr. Solutions Engineer and P4 Evangelist, Perforce), featured insights from Colin Walder (Engineering Director, CD PROJEKT RED), Joshua Orellana (Head of Animation and Games, Halon Entertainment), and Matt Ellis (Game Dev Advocate, JetBrains).

Today’s application development requires today’s test data management best practices. This is especially true for organizations embracing cloud-based application development. So, what can you do to improve your test data management practices? Start here, with our top best practices for test data management.

Enterprises working in Microsoft Azure need to mask data, and they need to mask it quickly.Yet, it can be difficult to find Azure data masking methods that are both swift and secure. The wrong approach can lead to bottlenecks, compromised analytics quality, and significant regulatory risks.