Transformation Plan Types
Ataccama ONE offers four transformation plan types. Use this page to pick the type that matches how you want logic to run and be reused.
Standalone plans
A standalone plan is a transformation you can execute or schedule on its own. It processes your data and writes results to a destination you choose.
At a glance:
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When to use: On-demand or scheduled processing where you control when the plan runs and where outputs go.
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How to create: Go to Data quality > Data transformations and select Create transformation plan > Standalone plan.
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How to run: From the three-dot menu on the Transformation editor tab, or schedule it for recurring execution.
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Output destinations: Database, file storage (for example, Amazon S3), or reference data table.
Example use cases:
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Nightly job that combines customer data sources, removes duplicates, and loads results into a master customer table.
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One-time data migration into your data warehouse.
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Weekly export of aggregated sales data to partner file storage.
Embedded plans
An embedded plan is reusable transformation logic that never runs by itself. You add it as a step inside other plans.
At a glance:
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When to use: Reuse the same logic across multiple plans. Updates to the embedded plan automatically propagate to every plan that references it.
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How to create: Go to Data quality > Data transformations and select Create transformation plan > Embedded plan.
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Where it appears: In the Plans list with an embedded badge, and as an Embedded plan step when building other transformations.
Example use cases:
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Phone number formatting logic reused wherever customer data is transformed.
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Standard address cleansing (trim whitespace, remove special characters).
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Common lookup logic for reference data enrichment.
Transformation catalog items
A transformation catalog item (TCI) is a catalog item whose data is generated dynamically by running its transformation logic. It does not persist data; it computes results each time someone works with the item.
At a glance:
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When to use: Always-current views without batch jobs.
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How to create: Create a new catalog item and select the transformation catalog item type, convert an existing item, or publish a preparation set on a source catalog item.
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Where to configure: On the Data Flow tab.
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When it runs: Automatically whenever you preview, profile, run DQ rules, export, or otherwise query the item.
Example use cases:
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De-duplicated customer view that stays current.
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Rolling sales summary combining multiple data sources.
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Unified product catalog merging data from several systems.
Transformation rules
A transformation rule is reusable logic that you apply to a source catalog item using a preparation set, producing a new transformation catalog item with the standardized results. Rules do not run or schedule on their own; they execute when the resulting transformation catalog item is processed.
At a glance:
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When to use: Enforce shared standards without duplicating logic across catalog items.
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How to create: Go to Data quality > Transformation rules and select Create transformation.
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Constraints: Each rule has one input and one output step and must keep the record count unchanged.
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How to apply: From a source catalog item’s Prepare data tab, create a preparation set and add the rule (see Prepare Data with Transformation Rules).
Example use cases:
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Normalize email addresses to lowercase across all customer-related catalog items.
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Standardize date formats across the organization.
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Mask sensitive fields for secure data views.
For more on creating and managing rules, see Transformation Rules.
Comparing plan types
| Feature | Standalone plan | Embedded plan | Transformation rule | Transformation catalog item |
|---|---|---|---|---|
Runs independently |
Yes (manual or scheduled) |
No |
No |
Yes (on access) |
Output storage |
Database, file, or reference data table |
Passed to parent plan |
Applied in TCI output |
Generated on demand |
Can be scheduled |
Yes |
No |
No |
No (updates automatically) |
Primary use case |
Batch processing |
Reusable logic |
Organization standards |
Always-current views |
Combining plan types
You can combine different plan types to build comprehensive workflows.
For example:
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Create an embedded plan with standard address formatting logic.
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Use that embedded plan inside a standalone plan that processes customer data nightly.
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Create a transformation rule that applies repeatable standardization logic.
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Apply that rule to a transformation catalog item that provides a secure, always-current view.
This modular approach lets you write transformation logic once and reuse it across your organization, reducing maintenance effort when business rules change.
Common transformation scenarios
The following pages walk through common transformation scenarios end-to-end, each using one or more of the plan types described in this article:
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Prepare Clean Reference Data for Lookups — Clean and load data into reference data tables using a standalone plan, with scheduled refreshes to keep the data current.
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Automate Recurring Data Processing — Schedule standalone plans for nightly exports, weekly aggregations, and other recurring jobs.
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Standardize Data Across Multiple Sources — Combine data from multiple systems using embedded plans to keep standardization logic in one place.
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Build Reusable Standardization Logic — Define logic once with embedded plans and transformation rules, then apply it everywhere.
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Create Always-Current Data Views — Use transformation catalog items to deliver virtual data views that compute results on demand.
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