Flashcards 3 — Joins & blending

What are fact table and Dimension table in Tableau?

These are data-warehouse terms rather than Tableau features, but Tableau is designed around them. A fact table holds the events you measure — order lines, transactions, support tickets. It is long and narrow: mostly foreign keys plus numeric values. A dimension table holds the things you slice by — Product, Customer, Date, Store. It is… Read the lesson

What is Data Blending?

Blending combines data from separate data sources into one view — a spreadsheet with a database table, for instance. The mechanics matter, because blending is not a join. Tableau queries each source independently, aggregates each one to the level of detail of the view, then combines the aggregated results on a shared dimension called the… Read the lesson

How many maximum tables can you join in Tableau?

Tableau allows up to 32 tables in a single join, and each table is limited to 255 columns. In practice you rarely approach that, and if you are close it is usually a sign the modelling belongs upstream. A view in the database that presents the joined result is faster and easier to maintain than a 20-table join defined in the workbook.… Read the lesson

What is data blending? When do you use this?

Blending combines data from separate sources by aggregating each one to the level of the view and then matching the results on a shared dimension. Use it when the sources genuinely cannot be joined — different databases with no cross-database connection, or a managed API alongside a warehouse table. It is also the better answer when the… Read the lesson

What is Assume referential integrity?

It is a setting under the Data menu that tells Tableau every row on one side of a join is guaranteed to have a match on the other. When it is on, Tableau can leave joined tables out of a query entirely if no field from them appears in the view. On a wide join that can cut query time noticeably, because the database is asked to do less… Read the lesson

Explain when would you use Joins vs. Blending in Tableau?

Join when the tables live in the same data source and share a granularity that will not fan out. A join happens in one query, gives row-level access to every field on both sides, and can be published as a single data source others reuse. Blend when the sources genuinely cannot be joined — separate systems, or managed APIs like Google Ads… Read the lesson

What is default Data Blending Join?

The default behaves like a left outer join from the primary data source. Every row from the primary is kept. Where the secondary has a matching value on the linking field, its aggregated result is brought across; where it does not, the secondary measures come through as null. Rows that exist only in the secondary do not appear at all.… Read the lesson

What do you understand by blended axis?

A blended axis puts two or more measures on a single shared axis rather than on two independent ones. You create it by dragging the second measure onto the axis of the first until the two green bars appear, which brings in the Measure Names and Measure Values fields. Because both measures are read against the same scale, the comparison… Read the lesson

How can we combine database and flat file data in Tableau desktop?

Connect to the first source, then in the data source page use Add next to Connections and connect to the second. Both then appear in the canvas and you can join them on a common field — a cross-database join. Tableau handles the mechanics by bringing the data together in its own engine, so you can join a SQL Server table to an Excel… Read the lesson

What type of join is used in data blending?

A blend behaves like a left outer join from the primary data source, though it is not literally a join — each source is queried and aggregated separately, then the results are matched on the linking field. Every row from the primary survives. Secondary values are attached where the linking field matches and come through null where it… Read the lesson

How do you normalize data for use in Tableau?

Normalising here usually means shaping the data so Tableau can work with it, rather than database normal forms. The most common operation is pivoting wide data to tall. A spreadsheet with one column per month needs those columns turned into rows of month and value before it can be charted — select the columns in the data source page and… Read the lesson

Which join is used in data blending?

A blend behaves like a left outer join from the primary data source. Rows from the primary are all retained; matching aggregated values from the secondary are attached where the linking field matches, and appear as null where it does not. Rows that exist only in the secondary are not shown. It is worth being precise in an interview that… Read the lesson

What is the criteria to blend the data from multiple data sources?

The requirement is a shared dimension — a field common to both sources that Tableau can match on, called the linking field. Tableau proposes links automatically where field names and types match. You can edit them under Data → Edit Blend Relationships, mapping fields whose names differ, and activate or deactivate a link by clicking the… Read the lesson

What is data blending?

Blending brings together data from separate sources by aggregating each to the level of the view and matching the results on a shared dimension. It is not a join. Each source is queried independently, so the two never meet at row level. The combination behaves like a left outer join from whichever source was used first in the sheet. That… Read the lesson

When to use joins versus Blending in Tableau?

Join when the tables are reachable from a single connection and the granularity will not fan out. One query, row-level access to every field, and the result can be published as a reusable data source. Blend when the sources cannot be joined — separate systems, or connectors like Google Analytics that Tableau manages as their own source —… Read the lesson