Google Cloud insights — from the delivery.

Your data is everywhere—except where you need it: How BigQuery lays the foundation for analytics and AI

Every department has its data, but no one has the full picture. Sales looks at the CRM, logistics at the ERP, marketing at five different tools — and every cross-functional question means someone spends days building a spreadsheet. According to Gartner, only 12 percent of companies have data of sufficient quality for AI applications. BigQuery on Google Cloud addresses exactly this problem: a central, maintenance-free data foundation that answers reports in seconds and feeds AI models from the same data.

Read more →~ 7 min

Your servers cost money at night too: Why serverless with Cloud Run turns the cost model upside down for many businesses

Traditional infrastructure is sized for peak demand — and costs the same every day as it does on that peak day. Serverless flips this model: you pay for what runs, and what doesn't run costs nothing. Cloud Run on Google Cloud makes this principle practical for everyday applications, without requiring teams to reinvent how they work. Here's how the cost model works, where its limits lie, and why we're writing about this from our own experience.

Read more →~ 8 min

Are We Even Allowed to Put This in the Cloud? What Google's Sovereign Cloud Means for German Companies

The most common question in German cloud projects isn't a technical one — it's a legal one: are we allowed to store our data there? Over the past few years, Google has built a remarkably concrete answer. €5.5 billion is flowing into German data centers and sites through 2029, Munich is home to the first Sovereign Cloud Hub, and the sovereignty portfolio ranges from EU data boundaries to fully air-gapped environments. Here's what you actually need — and how to answer the question properly.

Read more →~ 8 min

The prototype worked, but production never go live: How AI projects are making the leap with Vertex AI

More than 80 percent of all AI projects fail — twice the rate of traditional IT projects. That's what the RAND Corporation found through interviews with data scientists and engineers. The root causes are almost never the models themselves. They are unclear objectives, weak data foundations, and the missing path from laptop to production. Why the step from pilot to production is the real hurdle, and how a platform like Vertex AI on Google Cloud shortens that journey.

Read more →~ 8 min