A key lesson was to measure what matters. From the outset, we defined clear success metrics—latency reduction, resource ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Google is moving quickly to a future of data modeling. Here's how paid search marketers need to approach the analytics shift. There’s a lot going on in the world of Google Analytics 4 right now, as ...

Just because your firm can use your existing data for AI risk modelling doesn’t mean you should. There’s a perception that AI can create accurate predictions based on any data set. That’s not always ...

If your are wondering how to handle large datasets and complex calculations in your spreadsheets. This is where MS Excel PowerPivot comes into play. PowerPivot is an advanced feature in Excel that ...

eSpeaks' Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

A practical guide to building AI prompt guardrails, with DLP, data labeling, online tokenization, and governance for secure ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...