Combine and transform your data.

ETL

Combine and transform your data.

From business users to IT, Domo makes it easy to join data and make it uniformly available for analysis, from a simple drag-and-drop user interface to complex SQL transforms.

ETL for everyone.

Domo comes with ETL built into the platform, and our ETL tools are accessible to everyone, regardless of experience.

Flexible options.

Create visual data integration flows and simple data blending operations or use MySQL or Redshift SQL expressions to transform your datasets.

Repeatable flows.

Build flows once, then automatically apply your business logic every time data updates and get alerts when data transforms fail.

Rapid results.

Create fast, responsive transformations with Domo’s Adrenaline engine and data science tools to extract new insights.

Explore and enrich your data with Magic ETL.

Domo’s ETL tools allow you to visually define and sequence operations, as well as cleanse, combine, and transform data sets—all without knowing SQL.

Simply drag and drop datasets, actions, and connections to visualize your data flows and define operations, previewing as you go.

Join large datasets from multiple platforms, combining fields from multiple tables into one dataset.

Use Domo’s data exploration tools to explore your data and perform simple manipulations without ETL, such as filtering and grouping.

Create advanced transformations with custom queries.

Write custom queries using Domo’s integrated SQL editor for MySQL and Redshift data transformation engines to clean, normalize, and aggregate data.

Refine scripts directly in Domo without having to switch back and forth between tools.
Use SQL commands for subqueries, advanced joins, and sub-selects.
Choose your own indexing and system tables.

Deploy custom scripts into your data science pipeline.

Data science capabilities are integrated into Domo’s ETL so you can add actions or scripts right where the data is prepared.

Write custom R or Python scripts for data science analysis.
Use built-in data science actions such as classification, forecasting, and multivariate outliers to build statistical models.
Import custom scripts.