Learning centre
Clear explanations, worked examples and primary sources from the team that builds Zingg. Start with the basics, or jump straight to the problem you’re solving.
No match yet. Try a broader word, or browse the topics below.
Three reading paths, in order. Pick the one that matches where you are.
Every topic gathers the guides, deep dives and how-tos we’ve published, from first principles to running it in production.
Definitions, related ideas and why it matters.
Similarity, probability, blocking and thresholds.
For CDPs, composable stacks and customer 360.
How MDM is changing, and where matching fits.
Healthcare, public data, supply chains and more.
Step-by-step guides for each platform.
Agents, LLM apps and knowledge graphs.
Plain-English definitions of blocking, golden record, survivorship and more.
Open the glossary →Flagship guide
Our complete guide: what entity resolution is, the eight-stage pipeline, a worked example with scores, how to measure quality, use cases by industry and what makes it hard. Written from building Zingg, with every claim sourced.
Read the guideVendor-neutral guidance for choosing, buying or building entity resolution.
Twelve questions that decide fit, and how to prove a tool on your data.
Read the guide →DecisionThe real engineering cost of writing your own matching.
Read more →Reality checkFive problems teams hit, from similarity metrics to clustering.
Read more →ShortlistThe open-source options for 2026 and when each fits.
Read more →How teams use entity resolution in production.
Lessons from building Zingg, from our newsletter.
Zingg is open source and runs inside your data platform.
