Domo Transformation and Orchestration

Transform raw data into intelligent pipelines

Orchestrate end-to-end automated pipelines using accessible transformation tools, while inherited security and governance work at every step to ensure your data is ready for AI.

See it in action Book a demo

Trusted by data-driven companies

Transform raw data into intelligent pipelines

Orchestrate end-to-end automated pipelines using accessible transformation tools, while inherited security and governance work at every step to ensure your data is ready for AI.

See it in action Book a demo Watch a Demo

Trusted by data-driven companies

Architecture Transformation Orchestration Security Governance FAQ

how it works

Architecture that scales

Refine your entire data ecosystem with Domo's flexible, reliable architecture. Easily clean, transform, and orchestrate governed data pipelines at scale, without ever sacrificing performance.

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Accessible transformation

Transformation for everyone

A more cost-effective approach to data transformation. Tackle complex, high-value work with the advanced SQL, Python, and AI tools you need, while empowering business users with governed, drag-and-drop workflows for their data prep. This dual approach reduces IT backlogs and enables faster, more efficient self-service across the organization

capabilities

Visual Pipeline Builder (Magic ETL)

Visually map out and connect every step of your data’s journey. Chain together multiple transformations and actions in an intuitive drag-and-drop interface to build complex pipelines without code. Use built-in sections and notes to document your logic, then extend an intuitive, drag-and-drop experience to business users, all within one governed environment that you oversee.

ETL and ELT

Write powerful SQL transformations and build complex data pipelines with full control over both the logic and the output method—from full replaces and appends to advanced partitioning and upsert configurations.

AI Analysis and Generative AI

Enrich your data pipelines by integrating a full suite of AI services directly into your workflows. Use Domo’s native models, bring your own custom model (BYOM), or plug into external platforms like Hugging Face. This open approach allows you to achieve true data science automation using the exact models you need.

Jupyter Workspaces

Empower your data scientists with fully integrated Jupyter Workspaces. Enable them to use their preferred interactive notebook environment to explore data, build sophisticated models, and visualize results using Python or R, all without leaving the Domo platform.

Intelligent Pipeline Optimization

Keep your data fresh without breaking the bank. Domo optimizes processing based on data inputs, and can automatically adjust to use different methods—like upsert, partitioning, full replace, or append—to optimize performance by only updating the relevant batches or micro-batches.

scalable orchestration and observability

End-to-end automated pipelines

Move beyond single transformations and automate entire data pipelines at any scale. Visually build, orchestrate, document and monitor complex, multi-step pipelines that can be saved and reused across the business. This eliminates time-consuming manual processes and ensures your team can reliably deliver enriched data as your business needs grow.

capabilities

Intelligent Scheduling and Triggers

Automate your data pipelines to run on a custom schedule, whenever an upstream dataset is updated, or on-demand via an API. This ensures your data is always fresh and delivered when you need it.

Reusable Pipelines

Build complex transformation logic once and save it as a reusable DataFlow. Apply this standardized logic across multiple data pipelines to ensure consistency and dramatically accelerate development.

Automated Data Lineage

Gain full visibility into your data ecosystem with an interactive map of how data flows. Instantly understand dependencies between datasets and troubleshoot issues by seeing where data comes from and where it goes.

Actionable Alerts and Notifications

Proactively monitor the health of your data pipelines with custom alerts. Get notified of successes, failures, or data anomalies via email, mobile, or Slack so you can take immediate action.

Connector Writeback (rETL)

Close the loop on your automation by sending transformed, enriched data back into other cloud systems like Salesforce, Workday, or Google Ads to trigger actions, update records, and operationalize your insights.

"The ETL view not only allowed us to map out our process flows, but it also allowed us to recognize patterns, redundancies, and find potential efficiencies that we can now implement to save us time and to streamline our workflows."

Roxana Boboescu

Director of Business Intelligence, Cenegenics

Enterprise-grade security and governance

Trust in every transformation

Build unwavering trust by starting with the governance you already have. Domo automatically inherits and enforces security policies from your cloud data warehouse, then layers on our own enterprise-grade tools like data lineage and quality alerts. This provides a comprehensive, end-to-end governance framework that gives you full control and confidence.

capabilities

Enterprise Authentication

Integrate Domo seamlessly into your corporate security framework. Manage user access with your existing single sign-on (SSO) provider, and retain ultimate authority over data privacy with advanced options like Bring Your Own Key (BYOK) for Azure users.

Personalized Data Permissions (PDP)

Gain complete control over data access. Enforce security at the row-level by creating dynamic policies, and at the column-level by masking or hiding sensitive data fields. These permissions persist through all transformations, allowing users to securely run DataFlows on the precise data they are authorized to see and use.

Data Certification and Lineage

Build trust in your data by allowing authorized stewards to certify datasets as official and reliable. Full data lineage provides a transparent audit trail, showing exactly how data was transformed from source to visualization.

Platform Monitoring & Observability (DomoStats)

Use Domo to analyze automatically captured metadata on content adoption, user activity, and data performance. Track lineage from source to destination and gain deep visibility into pipeline performance, usage, and impact with system-generated DomoStats to optimize your analytics investment.

Data Quality & Health Monitoring

Proactively ensure the integrity of your data pipelines and automatically monitor datasets for issues like schema changes, row count anomalies, or data freshness. Trigger alerts so your team can catch and fix issues before they impact business decisions.

Comprehensive Audit Logs

Maintain a searchable record of all activity within your Domo instance. Track logins, view histories, data changes, and more to simplify compliance audits and gain full visibility into data usage.

Sandbox and Lifecycle Management

Safely manage your content development lifecycle with full versioning and change history for every asset. Enable teams to develop and test in a dedicated sandbox, then promote content to production with a governed release process. With planned GitHub integration, you will be able to sync your Domo projects with your own repositories for even greater control.

Trusted by industry experts

FAQ

We have answers

How is Magic ETL different from using spreadsheets for data prep?

While spreadsheets are familiar, they are manual, error-prone, and not scalable. Magic ETL transforms data preparation into a visual, repeatable workflow. You can process millions of rows, save and reuse your logic, and document every step, providing a level of governance and efficiency that spreadsheets can't match.

Can our technical team still use code for highly complex transformations?

Absolutely. Domo is designed for both accessibility and power. While Magic ETL handles most use cases with no-code, your data professionals have full access to SQL, Python, and R scripting within MagicETL as well. They can write custom, high-performance transformations and embed them directly into data pipelines, ensuring maximum flexibility for your most complex challenges.

If business users can transform data, how do we prevent a "data free-for-all?

Domo is built on a foundation of centralized governance. You can certify official datasets to guide users to trusted sources. Full data lineage shows exactly how data is being used and transformed. And with Personalized Data Permissions (PDP), you retain granular, row-level control, ensuring users only ever see the data they are authorized to, even during transformation.

What's the difference between a "transformation" and an "orchestration”?

A transformation is a single-purpose set of actions, like cleaning a column and joining two datasets. An orchestration is the automation of the entire end-to-end process. In Domo, you orchestrate by chaining multiple transformations together, setting them to run on a schedule or trigger, and adding alerts and notifications, turning a manual, multi-step task into a reliable, automated data pipeline.

How well do these visual workflows perform with very large datasets?

Domo's transformation tools are built on a high-performance, scalable architecture. Rather than pulling massive datasets into a memory-limited tool, Domo pushes the processing down to the data warehouse layer, leveraging its power and scalability. This means you can build and run complex transformations on millions or billions of rows with speed and efficiency.

Does Domo replace our existing dedicated ETL/ELT tool?

It can, but it doesn't have to. Domo is a full-stack platform that can manage the entire data journey, from ingestion to transformation and visualization, which can simplify your data stack. However, it is also designed to be flexible. You can use Domo to orchestrate and enhance your existing ETL/ELT processes, bringing modern self-service capabilities and governance to your current investments.

Here's what our customers are saying about Domo

See Customer Stories

“Visually seeing where everything was at, our pipeline, and our workflows got us moving a lot faster.”"What used to take 2.5 days now takes one hour.”