A relationship is the connection between two tables that says how their rows match up. Each order has a customer ID; the customer table has one row per customer ID; the relationship tells the tool that these are the same customers. Once it is defined, a chart can show order value by customer region even though “order value” lives in one table and “region” in another. Relationships are the building blocks of a data model.
Relationships are what let one question span several systems. A retailer’s sales come from its point-of-sale, costs from its ERP and store details from a spreadsheet. Related on product code and store ID, they answer “margin by store by category” in one chart. Without the relationship, someone recreates that join in a spreadsheet each week with lookup formulas, and one bad code breaks the whole sheet silently.
The common confusion is direction and count. Most relationships are one-to-many: one customer, many orders. Getting it backwards, or relating two tables that both have many rows per key, double-counts totals — the classic “revenue doubled overnight” bug. Rule of thumb: relate on an identifier, not a name; check a known total after adding each relationship; and keep the set small, because five well-chosen links beat twenty guessed ones.
In Klayara, relationships are drawn between tables from any sources — a database table to an imported spreadsheet, for example — and can be suggested automatically from matching columns, after which every dashboard can use them. See connectors and dashboards.