Map and transform, then review every typed row — errors flagged before Salesforce sees them.
Join up to five source files, reuse mappings, transform and group rows, and review typed values plus conversion or restricted-picklist errors. Download a prepared load workbook, or separately confirm a Bulk API 2.0 insert or External-ID upsert.
Real source files never start clean. INQUA turns the spreadsheets you actually receive — multiple files, mixed encodings, duplicate rows, text dates, currency strings — into reviewed, typed, load-shaped data. And the whole configuration is saved, so next month's file takes minutes, not another afternoon in Excel.
Define the target shape once, map and transform your source, and review before anything is delivered. The target you start from sets the destination: an uploaded load workbook produces a typed workbook from your source data; a target generated from Salesforce object metadata can run a reviewed Bulk API 2.0 insert or External-ID upsert.
Upload the Excel load template your downstream process already uses — no Salesforce connection required — and label its header rows once, picking each column's data type. Or connect and generate a target straight from a live Salesforce object's createable field metadata. Every prepared workbook reproduces the uploaded template's header block and formatting.
Upload one source file, or join up to five by key columns with match rates shown before you commit. Columns auto-map by name and AI suggests the rest — from metadata only, never your row values. Then refine: constants, combined fields, conditional rules, thirteen chainable transformations including whole-value mapping, and row selection that filters, de-duplicates, or flattens grouped rows.
Preview typed rows with per-cell errors flagged — conversion failures and values a field's picklist won't accept. Prepared workbooks run a full selected-row preflight scan first. Salesforce uploads show the exact target object and row count before a separate confirm, insert new records or upsert by an External ID — never delete — and are refused outright while any cell error remains. Even an accidental identical re-upload is caught and blocked.
Five screens from the real product — the exact flow you'd follow with your own files, from load template to reviewed import output.
Both paths use the same mapping, transformation, selection, and validation pipeline, but the target type decides the final step. This product does not export records from Salesforce.
Upload the Excel load template your process already trusts, map your CSV or Excel source onto it, and generate a typed workbook from those uploaded files. The original header block and formatting are preserved. No Salesforce connection or record retrieval is involved; you load the finished workbook with the approved tool your process already uses.
Build a target from a createable Salesforce object's metadata and accepted picklist values. After preview and review, run a separately confirmed Bulk API 2.0 insert or an upsert matched on an External ID — never a delete. For a round trip, create a Salesforce re-export elsewhere, upload it here, and the Reverse workflow can reshape it with the assigned record IDs for follow-on loads.
Open only the options a difficult migration needs, and leave the rest alone for a simple file.
A primary file plus four lookups, joined on key columns — with match rates and unmatched samples shown before the import exists.
Trim, case, find & replace, exact-format date parsing, whole-value mapping, and more — ordered per column, with a live sample of the result.
Keep matching rows, collapse groups to one row each, and pull a value from a sibling row — fourteen operators, all reviewed before delivery.
No Salesforce connection needed — upload a load template, map a CSV or Excel file, and download the reviewed workbook.
Speed only helps if you believe the result. The default Data Import workflow makes the source, row logic, transformed values, validation, and final delivery boundary visible.
Every import shows mapped fields, transformed samples, kept rows, configuration warnings, and per-cell errors before delivery.
Data Import uploads, templates, prepared workbooks, and saved recipes are private to your account and stay separate from other users' files.
Preparing a workbook never writes to Salesforce. A direct load runs only after you review and explicitly confirm — insert or External-ID upsert, never a delete — and an accidental identical repeat is refused.
Upload and map in the browser with no installer and no Salesforce connection required. Connect only for object-metadata targets or a reviewed direct load.
Admins carrying the import queue, operations teams standardizing recurring source files, and consultants migrating whole books of business. If that sounds familiar, it was built for you.
Use it for recurring Salesforce imports, data preparation for Salesforce migrations, and one-time cleanup-heavy loads across accounts, contacts, leads, tasks, and custom objects.
The Data Import Wizard accepts CSV files, supports a defined object set, and caps an import at 50,000 records. Data Loader covers broader bulk DML, record export, database and file inputs, and automated processing.
INQUA focuses on joining, transforming, grouping, and validating source files. It scans every selected output row for conversion and restricted-picklist errors before a prepared workbook or direct load can proceed.
Merging exports with VLOOKUP, trimming whitespace, fixing dates, de-duplicating contacts, re-checking it all after every mistake — the load itself is the easy part; the preparation eats the afternoon.
Joins, transforms, and row rules live in the import itself — no org connection needed. Next month, replace the source file and the whole configuration reruns.
Households, accounts, contacts, and legacy exports often spread one destination record across several rows or files. A flat loader cannot decide which row should win or where a sibling value belongs.
Group rows, prefer or require a matching row, and pull a mapped value from a specific or condition-matched sibling before the file reaches Salesforce.
INQUA is free while in early access — every tool included. When billing launches it will be one simple per-user price — well below platform AI tiers, BI licenses, and per-seat cloud loaders — and early-access users hear about launch pricing first.
Where the line sits, before you find out the hard way.
Data Import inserts new records or updates existing ones by an External ID you choose (upsert). Deletes do not exist in the product; use the tool your change-control process already trusts for that.
The prepared-workbook path reshapes files that you upload; it does not retrieve CRM records. Reverse also starts with a Salesforce re-export that you create elsewhere.
Every import runs on demand, after you review and confirm it. If you need recurring multi-system syncs, a dedicated ETL platform is the right fit.
Security isn't a feature we added; it's how INQUA is built. Workbook preparation stays separate from Salesforce. Direct Data Import writes sit behind a reviewed confirmation — insert or External-ID upsert, never a delete.
Upload a load template, map a source file, validate the selected rows, and prepare a typed workbook. Connect later only if you want object-metadata targets or a direct load.
Yes. Data Import reads .xlsx and .xlsm workbooks natively, along with .csv and .txt files. It detects common text encodings, drops blank rows, and reads cached Excel dates, numbers, and formula values. Legacy .xls files need a one-time re-save as .xlsx.
No. It does not retrieve Salesforce records and export them to CSV or Excel. The workbook path generates a typed, load-shaped workbook from source files and a load template that you uploaded. The direct path sends those prepared rows into Salesforce. Reverse requires you to upload a Salesforce re-export that you created elsewhere.
No. Upload the Excel load template your process already uses, map your source files onto it, and download the reviewed, typed workbook. Connecting Salesforce adds a separate target type built from createable object metadata and accepted picklist values, with optional Bulk API 2.0 inserts and External-ID upserts.
It can update — but only as an upsert matched on an External ID field you pick, so re-running a load updates existing records instead of duplicating them. It can never delete. Every upload still requires a preview, a review naming the target object and exact row count, and a separate explicit confirmation — and a payload identical to your last upload is refused unless you explicitly allow the repeat.
Yes. A primary file drives the rows and up to four lookup files join by key columns — with match percentages, empty-key counts, and sample unmatched keys shown before the import is created, so you see data-quality problems before a single record exists.
Field matching sends output-field metadata and source header names — never source row values. The opt-in value-matching tool is a separate disclosed action that sends the distinct values of one chosen source column plus the target's accepted picklist values. Suggestions remain unsaved and reviewable.
For preparation-heavy inserts and External-ID upserts, yes. INQUA adds native Excel input, multi-file joins, reusable mappings, transformations, row rules, and typed preflight review. Keep Salesforce Data Loader for record exports, update by record ID, delete or hard delete, and command-line automation.
Data Import stores your private source uploads, output templates, prepared workbooks, and saved recipes until you remove them. Account deletion removes the active application copies.
Create an account and start with just a file — no Salesforce connection required. Build a reusable mapping, validate the selected rows, and prepare a typed workbook; connect later for an optional direct insert or External-ID upsert.