Systems | Development | Analytics | API | Testing

Data masking vs. tokenization — which should your organization be using to protect sensitive data? The simplest answer: if you need to easily re-access original data, tokenization is preferable. If you need irreversibly transformed data for development or analytics, masking is the superior choice. This is especially true when it comes to using data for artificial intelligence (AI).

As AI becomes embedded in software delivery, the gap between mature DevOps organizations and those with “Incomplete DevOps” is becoming impossible to ignore, according to Perforce's 2026 State of DevOps report. Characterized by inconsistent workflows, manual processes, and inadequate standardization, "incomplete DevOps" has emerged as the leading obstacle to achieving ROI from AI investments. DevOps maturity is no longer an operational concern. It is an economic one.

Data virtualization can help modern organizations solve the complex challenges that come with managing data. With information scattered across multiple systems, accessing data can lead to operational bottlenecks in your organization.

High-Performance Computing (HPC) has traditionally been an exclusive club. If you wanted to run massive simulations or crunch petabytes of data, you had to leverage the predominant languages used on supercomputing hardware—usually C, C++, or Fortran. Although fast and efficient, these languages demand strict memory management and complex syntax that require strong software development skills. Without them, development time can slow down significantly. But the landscape is shifting.

Provisioning data for software testing requires balancing realism against security. Teams need production-like data to validate applications effectively. But they also have to adhere to strict privacy regulations. Two of the leading methods for creating and securing test data are data masking and synthetic data generation. Data masking de-identifies sensitive production data, preserving its scale, realism and referential integrity.

I've lost count of how many times I've heard some version of this story: A development team needs to spin up a new environment for testing, but the request often sits in a queue for days — sometimes weeks — while infrastructure teams wrestle with storage constraints and provisioning bottlenecks. By the time the environment is ready, priorities have shifted, sprint deadlines have been missed, and the team that requested it is already firefighting the next production issue. The kicker?

I have spent years working alongside enterprise leaders who face a common dilemma: the need to innovate faster while contending with strict compliance regulations and soaring infrastructure costs. In my experience, the biggest bottleneck isn’t a lack of ideas or talent. It’s data. Teams wait days or weeks for the data they need to build and test. That’s why I am excited to share how Perforce Delphix solves this challenge.

For many organizations, HostAccess plays a critical role in connecting modern systems with core enterprise environments. When software sits at the center of daily operations, stability and security are not optional. They are foundational. The HostAccess 7.50a release is more than a routine update. It represents a meaningful improvement in security readiness, compliance alignment, and long-term operational risk reduction.

In the semiconductor world, “software" is more than just application code. It is a complex stack of firmware, bootloaders, microcode, drivers, and Board Support Packages (BSPs) that are intricately linked to the hardware being designed. To secure the supply chain, meet customer expectations, and maintain market access, semiconductor leaders need a dynamic, "living" SBOM strategy that assesses risk in real-time and provides a single source of truth for all teams to work from.