Systems | Development | Analytics | API | Testing

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Key Takeaways Enterprise data teams spend millions on warehouse infrastructure while still designing schemas the way they did in 1995—one entity at a time, one relationship at a time, hoping the model survives its first encounter with production data. The irony runs deep: organizations racing to deploy real-time analytics are bottlenecked by modeling processes that take six to eight weeks before a single pipeline runs. Data warehouses succeed or fail on design.

In part one of this series, we walked through how to use Showcase in a Rails app. It's now time to read some Ruby code written by experienced Rails developers. To do this without getting lost, we'll choose one feature of the showcase engine and analyze how it works: rendering a preview of a component. Let's get started!

In Europe, trust is everything, and the bar is set by law. GDPR, the AI Act, NIS2, DORA, and the Data Act shape how data and AI must operate. Leaders need to show where data lives, who can touch it, and how it moves, and they want cloud speed and flexibility without giving up control, so sovereignty and transparency must be built in from day one.

Healthcare organizations are under growing pressure to connect legacy EHR (Electronic Health Record) and ERP (Enterprise Resource Planning) systems while safeguarding patient privacy and meeting strict compliance standards. Most of these systems — Epic, Cerner, MEDITECH, Infor, Oracle, SAP, and others — rely on enterprise-grade databases like Oracle, SQL Server, IBM DB2, SAP HANA, InterSystems IRIS, and PostgreSQL.

Federal agencies are right to prioritize commercial off-the-shelf (COTS) solutions for procurement modernization. Recent executive orders have provided a clear mandate for 'buy before build'—steering agencies toward proven, market-ready technology to accelerate mission delivery. But not all off-the-shelf procurement solutions are created equal. The technology landscape has evolved, revealing a critical divide in the world of off-the-shelf acquisition software.

Query templates in BigQuery data clean rooms let you create pre-defined queries that run against specific tables, reducing the risk of data exfiltration.

For the tenth consecutive time, Gartner has named Google Cloud Apigee a Leader in the 2025 Gartner Magic Quadrant for API Management.

A few years ago, we looked across many deployments and noticed a pattern: teams would build prototypes, spin up ML pipelines, and then stall. The model’s accuracy dropped. The “aha insights” dried up. The data scientists would get stuck waiting for dashboards to refresh, or data to be cleaned.AI is sexy. It sells. But it doesn’t do itself. The missing piece? Data readiness. Not just fast data.

The term “Behavior Driven Development”, or BDD, is an umbrella term for a wide variety of techniques. The general principles of BDD include reframing tests as descriptions of system behavior – “when I do one thing, I should see this result”. Historically, those descriptions were the output of a computer program. Over time, the uses of BDD shifted toward Gherkin, an English-like but precise language.