Infoveave Data Automation — Column Operations
Map old names to new ones once — every run through your workflow uses the names you actually want.
Data from external vendors, legacy systems, and different source tools rarely arrives with the column names your team expects. Rename Columns lets you fix that once inside your workflow: map the cryptic or inconsistent source headers to the names your dashboards, reports, and downstream activities rely on — and the mapping applies automatically on every subsequent run without anyone touching the file first.
Rename dataset column headers using a visual mapping in Infoveave workflows. Standardize inconsistent field names from external sources without writing SQL or code.
Rename Columns is one step inside a multi-step Infoveave workflow. Chain it with other activities — no code, no manual hand-offs.
Build this workflow visually in Infoveave Data Automation — drag, connect, and schedule with no infrastructure setup.
Real scenarios where this transformation saves hours of manual work.
A plant operations team receives hourly machine logs with field names assigned by the sensor vendor — t1, t2, rpm_a, and so on. Rename Columns maps those to Temperature Inlet, Temperature Outlet, and Motor RPM at the start of every workflow run, so all downstream aggregation and alerting steps work against consistent, human-readable headers.
A retail analytics team ingests product feeds from three different suppliers, each using different column naming conventions. Rename Columns normalizes all feeds to a single schema — Product ID, Name, Category, Price — before any transformation step, eliminating the need to maintain separate workflow branches for each supplier format.
A healthcare data team exports patient records from an EHR system with abbreviated field names like pt_id, adm_dt, and dsc_dt. Rename Columns maps these to Patient ID, Admission Date, and Discharge Date before the data enters the analytics warehouse, ensuring report templates and QA checks match expected field names without manual pre-processing.
Input data (left) is transformed using the configuration below. The output table (right) is ready for dashboards or downstream steps.
id -> index, product -> resultInput Data
| id | category | product | price | available |
|---|---|---|---|---|
| 1 | Electronics | Laptop | 500 | true |
| 2 | Electronics | Camera | 350 | false |
| 3 | Furniture | Sofa | 600 | true |
Output Data
| index | category | result | price | available |
|---|---|---|---|---|
| 1 | Electronics | Laptop | 500 | true |
| 2 | Electronics | Camera | 350 | false |
| 3 | Furniture | Sofa | 600 | true |
Key fields to configure in the Infoveave workflow builder. Full reference available in the documentation.
Column Map
Define pairs of original column names and their replacement names. You can rename as many columns as needed in a single step. Columns not included in the mapping are left unchanged — rename only the headers that need updating and everything else passes through untouched.
Selective Renaming
Only the columns listed in the Column Map are renamed. All other columns retain their original names and values, so you can safely apply a partial rename without affecting fields that are already correctly named.
Everything you need to know about Rename Columns in Infoveave.
Transformations in the same family as Rename Columns, often chained together in the same Infoveave workflow.
Part of Infoveave Data Automation
Rename Columns is one of over 80 transformation activities available inside Infoveave workflows. Chain transformations together — no code, no exports, no waiting for IT.
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