Data is the lifeblood of modern businesses, but raw data alone doesn’t tell you much. To unlock its potential, you need analytics—the process of turning data into actionable insights. Analytics can be broken down into four key types: descriptive , diagnostic , predictive , and prescriptive . Each type answers a unique question about your data and plays a critical role in helping your business make smarter decisions. In this post, we’ll explore what each type of analytics does

“AI-ready” data is more than clean tables sitting in the cloud. It’s data that’s readable by machines, governed with intent, enriched with business context, and supported by an architecture flexible enough to power many focused models. In this guide: What AI-Ready Data Looks Like—and what breaks when you don’t have it How to Make Your Data AI-Ready A Self-Assessment to Gauge Your Readiness What AI-Ready Data Looks Like (and What Goes Wrong Without It) AI-ready data creates fa