👋 Welcome from CIFL (2024)

FAQs

How do you use blended data? ›

Steps for blending data

To create a blend in a workbook, you need to connect to at least two data sources. Then bring a field from one data source to the sheet—it becomes the primary data source. Switch to the other data source and use a field on the same sheet—it becomes a secondary data source.

Method 1: Combine Charts

It is the easiest way for you to combine multiple data sources in Google Data Studio. You can simply put the charts that you've created into one chart. It becomes a very useful approach when you've already created separate charts, and you want to bring them together.

Data blending is the process of combining data from multiple sources into a functioning dataset. This process is gaining attention among analysts and analytic companies because it is a quick and straightforward method used to extract value from multiple data sources.

Blending data lets you create charts, tables, and controls based on multiple data sources. You can blend up to 5 tables. 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.

Blending data from these sources into one data set quickly reveals relationships and preliminary data analytics trends that can be immensely useful to business users. In this case, it might be something as simple as demographic details that leads and existing customers have in common.

Unlike joins, blends do not combine the data from multiple tables into a single table. Blends link tables together visually, allowing you to see the combined data in views and dashboards, but the data is not merged at the row level. For example, you have a transaction sales table and a date table with one row per day.

Is there a free version of Looker? ›

Looker Studio is a free tool that turns your data into informative, easy to read, easy to share, and fully customizable dashboards and reports.

Data blending has some limitations regarding non-additive aggregates such as COUNTD, MEDIAN, and RAWSQLAGG. Non-additive aggregates are aggregate functions that produce results that cannot be aggregated along a dimension. Instead, the values have to be calculated individually.

Last December, Google rebranded “Google Data Studio” to “Looker Studio” after acquiring Looker earlier in February 2021. Looker and Looker Data Studio are both Google tools with a lot in common.

Data blending operates with two main data sources: primary and secondary data sources. The primary data source is the one at the left of the LEFT JOIN statement, and the secondary data source is the one at the right of the statement.

Duplicate data after a join is a symptom of data at different levels of detail. If you notice duplicate data, instead of creating a join, use data blending to blend on a common dimension instead.

Unlike an ordinary join, which combines data sources at the lowest granularity before any aggregation is done, a data blend can join data sources after aggregation is performed on the individual sources; ultimately limiting the number of records that are joined together and maximizing computational efficiency.

Extract, transform, load

Both ETL and data blending take data from various sources and combine them. However, ETL is used to merge and structure data into a target database, often a data warehouse. Data blending differs slightly as it's about joining data for a specific use case at a specific time.