---
title: "Data Blending"
slug: "data-blending"
description: "Merge two different data sources with Dataddo. Learn how to blend sources, configure joining types, and troubleshoot errors. Get help from our experts."
updated: 2025-10-31T16:13:17Z
published: 2025-10-31T16:13:17Z
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dataddo.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Data Blending

**Data blending** integrates data from two ***data sources*** based on common identifiers or keys. This approach combines complementary data from different ***sources*** to form a single view, similar to the `JOIN` operator in SQL.

## Create a New Data Flow with Blending

1. Navigate to the Flows page and click on **[Create Flow](https://app.dataddo.com/flow/new)** in the top right corner.
2. Click on **Connect Your Data** and select the first source.
3. Hover over the newly added source for the menu to show and click on **Combine**.
4. Select **Blend Sources**.
5. Click on **Select Source** to choose the sources you wish to blend.
6. Choose a **Join Key** that is the same for both sources. Dataddo will blend the datasets based on this particular key.
7. Click on the **button between the sources** to configure the joining type. **Left Join** is selected by default.
  1. **Left Join**: Records from the right source will be joined **to the left** dataset.
  2. **Inner Join**: Returns records which values are only **matching in both column sources.**
8. Click on **Save Source**.
9. Add your ***data destination***, finish configuring your flow, and click on **Save Flow**.

![Data Flows - Click on Combine](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Data%20Flows%20-%20Click%20on%20Combine.png)

![Data Flows - Celect Data Combination Method](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Data%20Flows%20-%20Celect%20Data%20Combination%20Method.png)

          **DATADDO TIP**

          

Select columns from each ***source*** by **dragging the fields** from the list on the left or right. The ***sources*** don't have to have the same columns.

![Data blending in app - step 7](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Data%20blending%20in%20app%20-%20step%207.png)

          **Editing a Flow**

          

If changes affecting the database schema are made **in the *flow*** (e.g. change in field names, number of columns, data types), go to the database and delete the previously created table. Then, save the changes and refresh.

---

## Troubleshooting

### Issue with Repeated Column Names

ERROR MESSAGE `The column name ‘___’ is specified more than once`

This problem can be fixed by renaming the affected column in one of the two ***data sources***.

1. On the [Sources](https://app.dataddo.com/sources) page, click on one of the ***sources*** you wish to blend
2. Navigate to the **Schema** tab, change the name of the affected column to e.g. **propertyid_2** and click on **Save**.

Your ***data sources*** can be blended as no column is defined twice anymore.

![Change column name/label](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Schema%20-%20Change%20column%20name.png)

### Duplicated Field

When using data blending, combining columns from two different ***data sources*** may result in a duplicated field (such as ID). This can result in a broken ***flow***. Rename one of the two affected columns like in [the previous troubleshooting guide](/docs/data-blending#issue-with-repeated-column-names).

A source is a collection of data from an authorized service that's been connected via a Dataddo connector. Data within the source is automatically refreshed based on the source's configuration.

A destination is the endpoint where the data from your sources will be loaded. Destinations include dashboarding tools, data warehouses, and other online services.

A data type, specified within a data source’s schema, determines the kind of value that can be stored in a column for organized data management. The available data types include integer, float, date, and string.