Select Columns
Infoveave Data Automation — Column Operations
List the columns you need. Everything else is gone — and the order in your list becomes the order in your output.
Most source datasets arrive wider than any downstream step needs. Select Columns gives you a clean projection of only the fields relevant to the current workflow — reducing data volume, removing noise from reports, and preventing unnecessary columns from complicating every transformation that follows. It also lets you control the column order in the output, so the data always arrives in the shape downstream systems and templates expect.
What Select Columns does
Retain only a chosen set of columns from a dataset in Infoveave workflows. Reduce dataset width, eliminate noise, and focus downstream steps on the fields that matter.
When to use Select Columns
- You are importing a wide dataset with 20 or more columns and only need a handful for your report or analysis
- You want to control the exact column order in the output before passing data to a database insert, API, or export template
- You are preparing a focused dataset for a visualization or dashboard that should only surface specific fields
- You want to drop all unneeded columns in one operation rather than individually listing each field to remove with Drop Columns
When to avoid it
- You only need to remove a few specific columns from an otherwise complete dataset — Drop Columns is simpler when you have more to keep than to remove
- You want to rename the columns you select — chain Select Columns with Rename Columns for that combination
- You need to filter rows rather than columns — use the Filter activities for row-level selection
Where it fits in your Infoveave automation
Select 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.
How teams use Select Columns
Real scenarios where this transformation saves hours of manual work.
Extract Key Dealer Columns Before Sales Summary
A retail analytics team imports a 20-column dealer performance file but only needs dealer name, facility type, country, region, state, and city for the regional sales summary. Select Columns reduces the dataset to those six fields at the top of the workflow, so all subsequent aggregation and visualization steps work against a clean, narrow table instead of a wide raw export.
Focus Machine Logs on Production KPIs
A plant data team pulls logs from a sensor platform that returns 35 columns per reading — most of which are diagnostic fields used only by the vendor's support team. Select Columns keeps only the KPI columns needed for OEE and throughput analysis, so the analytics workflow processes a lean dataset on every scheduled run instead of handling 35 fields when only 8 are relevant.
Project Transaction Fields for Reconciliation Template
A finance team feeds processed transactions into a reconciliation spreadsheet template that expects a fixed set of columns in a specific order. Select Columns projects only the required fields — Transaction ID, Date, Amount, Account, and Status — and arranges them in the order the template requires, preventing column ordering mismatches that caused paste errors when the export was done manually.
See Select Columns in action
Input data (left) is transformed using the configuration below. The output table (right) is ready for dashboards or downstream steps.
SI No, Dealer Name, Facility Type, Country, Region, State, CityInput Data
| SI No | Date | Group | Dealer Code | Dealer Name | Facility Type | Country | Region | State | City | Model | Variant | Fuel | Price | Quantity |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2023-02-28 | GRP-A | N_001 | Asia Automobile | Showroom | India | North | Jammu & Kashmir | Srinagar | Glow | LXI | Petrol | 1000 | 10 |
| 2 | 2023-03-31 | GRP-A | N_001 | Asia Automobile | Showroom | India | North | Jammu & Kashmir | Srinagar | Glow | LXI | Petrol | 1000 | 10 |
Output Data
| SI No | Dealer Name | Facility Type | Country | Region | State | City |
|---|---|---|---|---|---|---|
| 1 | Asia Automobile | Showroom | India | North | Jammu & Kashmir | Srinagar |
| 2 | Asia Automobile | Showroom | India | North | Jammu & Kashmir | Srinagar |
Configuration
Key fields to configure in the Infoveave workflow builder. Full reference available in the documentation.
Columns to Select
List the column names you want to keep. All other columns are excluded from the output. The order of columns in the output matches the order you specify here — meaning you can also use Select Columns purely to reorder columns without adding or removing any fields.
Order Control
The column sequence in the output matches exactly the order in your selection list. If you list Dealer Name before Country, Dealer Name appears first in the output — regardless of the original column order in the source dataset. This makes Select Columns useful for reformatting column layout without a separate Move Columns step.
Frequently asked questions
Everything you need to know about Select Columns in Infoveave.
Also in Column Operations — and what runs before & after
Transformations in the same family as Select Columns, often chained together in the same Infoveave workflow.
Part of Infoveave Data Automation
80+ transformations. Zero manual steps.
Select Columns is one of over 80 transformation activities available inside Infoveave workflows. Chain transformations together — no code, no exports, no waiting for IT.
Ready to see Infoveave in action?
