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A batch of the best highlights from what Kevin's read, .

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How to Create Enterprise Data Warehouse Software

Yuliya Melnik

A knowledge graph is made up of three main components: nodes, edges, and labels. Any *object*, *place*, or *person* can be a **node**. An **edge** defines the *relationship* between the nodes. For example, a node could be a client, like IBM, and an agency like, Ogilvy. An edge would be categorize the relationship as a customer relationship between IBM and Ogilvy. A represents the subject, B represents the predicate, C represents the object

What is a knowledge graph?

ibm.com

Here’s what the entity resolution query looks like: ![](https://substackcdn.com/image/fetch/w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F97ec307e-6b10-46fd-8b6a-773f9f163875_1212x728.png) I’m joining the table with itself on state + zipcode to reduce the search space and using string similarity thresholds for filtering potential duplicates. In entity resolution methodology this is known as “blocking.”

Fundamental Data Engineering Concepts - Part 2

Ergest Xheblati

...catch up on these, and many more highlights