Blend Table Document For Free

Data integration typically refers to more comprehensive data cleansing and merging across different sources. Data blending is typically for conducting quick, surface-level analysis of data. On the other hand, data integration typically applies to warehouse settings when you need to bring together multiple joins.

Data Blending is a very powerful feature in Tableau. It is used when there is related data in multiple data sources, which you want to analyze together in a single view. As an example, consider the Sales data is present in a relational database and Sales Target data in an Excel spreadsheet.

Blending data lets you create charts, tables, and controls based on multiple data sources. For example, you can blend data from different BigQuery tables?say customer information and order details?and visualize that information in a single Looker Studio table.

The simplest way to think of data blending is as an aggregated outer join. However, rather than creating a physical join of your data set, a data blend is a view of an aggregated join from disparate data sets. Data blending is a very useful tool, but there are some effects on performance and functionality.

Data Blending Aggregates the data and then combines it. Joins combine the data and then aggregates it. Data Blending can combine data from different sources. Joins can combine data from the same sources only.

Data Blending vs Data Joining in Tableau - YouTube YouTube Start of suggested clip End of suggested clip And any rows from the right table that has a corresponding row match in the left. Table the resultsMoreAnd any rows from the right table that has a corresponding row match in the left. Table the results are then sent to tableau to be aggregated. For example suppose you have the following tables.

The main difference between the two is when the aggregation is performed. A join combines the data and then aggregates. A blend aggregates and then combines the data.