Data TransformationColumn OperationsBeginner

Rename Columns

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.

Input:Tabular dataset with original column headersOutput:Tabular dataset with updated column names (data values unchanged)

What Rename Columns does

Rename dataset column headers using a visual mapping in Infoveave workflows. Standardize inconsistent field names from external sources without writing SQL or code.

When to use Rename Columns

  • You receive data from external vendors or APIs with cryptic field names like col1, field_A, or unnamed system codes
  • You are merging data from multiple sources and need consistent column names before joining or aggregating
  • You want to align incoming column headers with the naming convention expected by a downstream database, dashboard, or report template
  • You need to add clarity before sharing or presenting a dataset — replacing technical abbreviations with human-readable labels

When to avoid it

  • You need to remove columns from the dataset entirely — use Drop Columns instead
  • You want to reorder columns without changing their names — Move Columns handles that
  • You need to create a copy of a column under a second name while keeping the original — use Copy Columns

Where it fits in your Infoveave automation

Rename Columns is one step inside a multi-step Infoveave workflow. Chain it with other activities — no code, no manual hand-offs.

ConnectRead data from CSV, Excel, database, or API into Infoveave
You are hereRename ColumnsMap original column headers to standardized names once and reuse on every run
Select / DropKeep only the relevant columns or remove unnecessary fields
TransformApply calculations, binning, aggregation, and other data shaping steps
AutomateSchedule the workflow to process and rename headers automatically on every import

Build this workflow visually in Infoveave Data Automation — drag, connect, and schedule with no infrastructure setup.

Infoveave — Workflow Builder
● SavedSchedule: Daily 06:00
Data SourceConnectRead data from CSV, Excel,…YOU ARE HERERename ColumnsMap original column header…Select / DropKeep only the relevant col…TransformApply calculations, binnin…AutomateSchedule the workflow to p…Dashboard

How teams use Rename Columns

Real scenarios where this transformation saves hours of manual work.

Manufacturing

Align Machine Log Headers to Plant Reporting Schema

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.

Retail

Standardize Product Feed Headers for Catalog Ingestion

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.

Healthcare

Map EHR Export Headers to Internal Data Warehouse Schema

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.

See Rename Columns in action

Input data (left) is transformed using the configuration below. The output table (right) is ready for dashboards or downstream steps.

Column Map:id -> index, product -> result

Input Data

idcategoryproductpriceavailable
1ElectronicsLaptop500true
2ElectronicsCamera350false
3FurnitureSofa600true

Output Data

indexcategoryresultpriceavailable
1ElectronicsLaptop500true
2ElectronicsCamera350false
3FurnitureSofa600true

Configuration

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.

Frequently asked questions

Everything you need to know about Rename Columns in Infoveave.

Also in Column Operations — and what runs before & after

Transformations in the same family as Rename Columns, often chained together in the same Infoveave workflow.

Part of Infoveave Data Automation

80+ transformations. Zero manual steps.

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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