Data Import and Export
Data import and export describe the recurring reading in (import) and writing out (export) of data during live ERP operation – usually as bulk processing via structured files such as CSV or Excel. Import fills the system with external data; export makes it available to other systems or reports.
Data import and export describe the regular, often bulk reading in (import) and writing out (export) of data during the live operation of an ERP system. During an import, the system takes on data from an external source – a supplier price list, a batch of orders or updated item data, for example – usually via structured files such as CSV, Excel or XML. During an export, the ERP conversely hands out data so it can be reused in another system, a report or by a service provider. Both are routine day-to-day operations, not one-off projects.
Characteristic is the processing in bundles (batch): instead of entering each record individually, a whole file with hundreds or thousands of rows is taken on or generated in a single run. Import and export are therefore a central tool for coupling an ERP efficiently with its environment, without needing a fixed programming interface for every data handover. They form the pragmatic bridge between manual single-record entry and fully automated system integration.
At a glance
- Import = read data in, export = write data out – during live operation
- Bulk processing in batches via file formats such as CSV, Excel, XML
- The heart of it is field mapping: file column ↔ ERP field
- A recurring routine task – to be distinguished from migration and integration
- Success factor: clean, valid data and stable templates
How data import and export work
An import starts with a source file whose structure the ERP has to understand. The user uploads the file or drops it into a monitored directory, assigns the columns to the target fields and starts the run. The system checks the data against rules – mandatory fields, formats, permitted values, unique keys – and reports faulty rows back instead of discarding the whole batch. An export works the other way round: the user selects a data range, filters it and defines which fields are written to the output file, and in what order.
So that an import correctly matches known data, it works with a key field (an item or customer number, for example): if the record exists, it is updated, otherwise it is created anew – often called an "upsert". Recurring import and export definitions are saved as templates or profiles, so the same operation is repeatable tomorrow without setting it up again. Advanced systems let such runs execute automatically on a schedule.
Field mapping and data formats
Field mapping determines which column of the file corresponds to which field in the ERP – for example "Item no." to "item number" or "gross retail" to "sales price". It is the heart of every import, because a wrong or shifted mapping writes correct data into the wrong fields. Common formats are CSV (simple, tabular, but sensitive to delimiters and character set), Excel (convenient for clerks), plus XML and JSON for structured, nested data. With CSV in particular, encoding (UTF-8), decimal and date format are typical sources of error.
Validation and error handling
A robust import validates every row before writing it and provides a log: records imported, updated and rejected, along with the reason. This lets faulty rows be corrected and the run repeated selectively, without importing already correct data twice. Idempotence is important – that an import accidentally started twice creates no duplicates but produces the same state.
Why data import and export matter day to day
Hardly any company enters all data into the ERP by hand. Prices, item data, orders, incoming payments or stock notifications often arise outside the system and have to get into it efficiently. A good import saves enormous entry time here and reduces typos, because hundreds of rows are taken on in seconds rather than hours. The export, in turn, supplies the tax advisor, logistics provider, marketplaces or reports with exactly the data they need.
For many small and mid-sized businesses, import and export are also the low-barrier substitute for expensive interface projects: as long as a daily CSV exchange suffices, no permanent API coupling has to be built. This makes the function an important building block for flexibility – for instance when a new sales channel is connected or a service provider is switched and a workable data bridge is quickly needed.
Data import and export in the ERP system
In an ERP, import and export touch almost all data areas. On the master data side, item, customer and supplier records are maintained or supplemented; on the transaction data side, orders, purchase orders, invoices or postings move in both directions. Typical uses are importing a supplier price list, reading in shop orders, exporting open items to accounting or outputting stock lists for a stocktake.
Because imported data takes immediate productive effect, data quality is the critical factor: faulty prices or wrongly assigned accounts propagate directly into documents. That is why test runs in a preview, mandatory-field checks and a meaningful error log are standard. In the DACH region the GoBD perspective is added: import and export operations that concern tax-relevant data should be traceable and logged, and exported accounting data has to match the tax advisor's formats (DATEV-compliant outputs, for example).
Distinction from migration and integration
Data import and export are recurring routine operations during live operation. Data migration, by contrast, is the one-off, project-like transfer of an entire dataset from a legacy system at a cut-off date – it uses import techniques but is not a day-to-day process. Integration, in turn, is the permanent, mostly automated data exchange between productive systems via an API or middleware, without a human touching files. Rule of thumb: migration is one-off, import/export is manual or semi-automatic routine exchange via file, integration is the permanent system coupling in real time.
Typical pitfalls and good practice
The most common problems are technical in nature: the wrong delimiter or wrong character set in CSV files, swapped comma and period notation in amounts, truncated leading zeros on item numbers in Excel, or inconsistent date formats. On the business side, dangers lurk in the mapping and in missing keys – without a unique key, an import quickly creates duplicates instead of updates.
It has proven worthwhile to maintain stable templates, to check every import first as a test run or preview, and to consistently evaluate error logs. Whoever documents import and export profiles and – where possible – automates them on a schedule makes the operations reproducible and less error-prone. As soon as a data exchange occurs daily and in large volume, the move from file to real integration via an interface is worthwhile.
Example
Example: price list and orders at a wholesaler
A B2B wholesaler receives an updated price list from its main supplier every month as an Excel file with around 8,000 line items. Instead of maintaining the new purchase and sales prices by hand, an import profile is stored in the ERP: the file is uploaded, the columns are permanently mapped to item number, purchase and sales price, and the run updates only existing items via the key field. An error log lists rows with an unknown item number, which are checked separately.
In the opposite direction, the same ERP automatically exports revenues and open items every evening into a DATEV-compliant file for the tax advisor, plus a shipping list for the logistics provider. What used to cost two days of typing per month now runs in a few minutes – the actual work lies in the template set up cleanly once and the review of the error logs.
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