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tricentis

Why performance validation is an infrastructure issue, too

Aug 12, 2026 By Annie Millerbernd In Tricentis
At Datadog DASH in the spring, the Tricentis NeoLoad team met folks in all types of roles – developers, test engineers, CoE leads, and SREs – and one recurring theme we found was that SREs often didn’t know much about how performance validation happens at their companies. That’s a fair division of labor. Seemingly, the performance team’s work would be related but not mission-critical to the infrastructure team’s. But that’s not entirely true.
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loadfocus

Cloud-Based vs On-Premise Website Monitoring: Which Approach Wins in 2026?

Aug 12, 2026 By LoadFocus In LoadFocus
Website monitoring often feels like choosing between casting a net or wielding a spear. Cloud-based monitoring is your fishing net: you deploy it broadly, covering vast swaths of digital water, capturing issues wherever they occur. It’s automated, relentless, and covers every corner of your online presence, from global uptime to minute performance blips. On the other hand, on-premise monitoring is the spear – deliberate, targeted, and controlled.
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integrate

Best GDPR Data Mapping Tools (2026): Requirements + Top Picks

Aug 12, 2026 By Donal Tobin In Integrate
GDPR data mapping has evolved from a one-time documentation exercise into continuous operational reality. With €7.1 billion in cumulative fines and regulators increasingly scrutinizing actual data practices versus paper compliance, organizations need tools that provide genuine visibility into where personal data lives, how it flows, and who processes it. The critical gap in most "GDPR compliance software" is that they help you document compliance without actually scanning your data infrastructure.
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integrate

Database Mapping Explained: Techniques, Tools, and Real Examples

Aug 12, 2026 By Donal Tobin In Integrate
Database mapping sits at the core of every successful data integration, migration, and ETL project. It's the blueprint that determines whether your customer records, sales figures, and operational data arrive accurate and usable, or quietly broken. With organizations managing dozens of data sources in mid-market environments, getting database mapping right has become essential for maintaining data integrity across increasingly complex tech stacks.
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hitachi vantara

Manage by Exception, Not by Exhaustion

Aug 12, 2026 By Nick Loy and Sushant Sawant In Hitachi Vantara
Ask any storage team what has changed over the last five years, and you'll hear a version of the same answer: everything grew and became more complex all at once. More applications, more data, more platforms, more places for a problem to hide. Complexity outpaced the teams meant to manage it. The staffing math makes it worse. Two-thirds of data center operators now struggle to hire or retain qualified staff.
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dreamfactory

How DreamFactory Helps Schools Use AI Safely on Their Own Data

Aug 12, 2026 By Kevin Hood In DreamFactory
Every school, college, and university is being asked the same question right now: Can we use AI on our own data without putting student records at risk? The promise is real, including personalized learning, faster advising, and smarter operations. So is the fear. AI that touches student information runs straight into FERPA, breach risk, and a simple trust problem: once data leaves your control, you can't govern it.
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Government API Use Case: How to quickly connect your application with Data.

Aug 12, 2026 By DreamFactory | AI & Applications Data Gateway In DreamFactory
Getting data out of source systems and into the applications that need it is usually slow, custom, and hard to secure. Today I'll show you how DreamFactory solves that as a secure data gateway. This demo today is based on a government healthcare use case.
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databox

Why Do AI Tools Give Different Numbers for the Same Question?

Aug 12, 2026 By Mateja Verlic Bruncic In Databox
You can ask two AI tools the same question about your data and get different answers, even when both have access to the same system. There are several reasons this can happen. Each one might run a different model, or have a different set of tools available. The data you thought was the same might not actually be the same. Or one tool might have more context about my account than the other. I want to focus on what happens after I rule those things out: each tool still has to decide what my question means.
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Agent Product Use Case - Slack & Jira Discrepancy Workflow

Aug 12, 2026 By ThoughtSpot In ThoughtSpot
Customers and champions report problems in Slack, but if nobody files the ticket, the issue disappears before it ever reaches Jira. In this video, we use AgentSpot to build a Slack to Jira Coverage Workflow that reads your champions channel every morning, cross-compares it against your Jira backlog, and emails you a report of every issue raised in Slack that no one has filed yet. What is AgentSpot? AgentSpot is an Agentic Workforce Platform for building workflows that make decisions, take action, and deliver results across every system your business runs on, grounded in your data.
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