GuidesContact
Guides

Moving data between two systems without typing it twice

CloudBuilder AI · 2 min read

Somebody enters an order into one system, then enters the same order into a second one. It is the most automatable task on the list and the one where projects most often stall, because the hard part is not the moving. It is deciding what counts as the same record.

Field mapping is the easy half

Mapping is the part everybody pictures: this field over here goes into that field over there. It is genuinely straightforward when both systems have an API, and it is where the 70 to 90 percent share in the calculator comes from. The work is tedious rather than difficult, and it is finite: a mapping done once keeps working until somebody changes a form. Most of the value of an automation project is delivered by this half, which is why it is worth doing even when the second half is messy.

Record matching is the hard half

The second system usually already has some of the records. So a build has to answer, for every row: is this a new record or an update to an existing one? Businesses answer that with an email address, a customer number, a phone number, or some combination, and every one of those is unreliable on its own. Two people share a family email address. A customer number was retyped with a transposed digit in 2019. A phone number was stored with a country code in one system and without it in the other. This is the work that makes a rekeying project take three weeks rather than three days.

What happens when it does not match

The important design decision is what a build does with an ambiguous record, and there are only two honest answers: refuse and queue it for a person, or merge and risk creating a wrong record. Refusing is almost always right. A duplicate customer record is a nuisance; a merged one that combines two real customers is a genuine problem that surfaces months later in a bill sent to the wrong person. A build that quietly merges on a fuzzy name match will look better in its first week and worse in its first year.

The direction matters more than people expect

One-way sync, where system A is the source of truth and system B follows, is a well-understood problem with a clean answer. Two-way sync, where either side can change a record, is a different and much larger problem: two people edit the same customer in two systems in the same hour and something has to decide which edit wins. Most businesses that ask for two-way sync actually want one-way sync plus one specific field flowing back. Establishing that is usually the single most useful hour of an audit.

What to check before committing to it

Whether both systems have documented APIs on the plan you actually pay for. Which system is the source of truth for each field, written down, because the answer is often different for different fields. And what your current duplicate rate is, which nobody knows until they look. If the second system is a desktop application with no API, the honest answer is usually that this is not worth automating, and the calculator will say so.

Related

Common questions

Can it sync both ways?
Technically yes, and it is a much bigger project than one-way. Two systems that can both change the same record need a rule for which edit wins, and that rule is a business decision rather than a technical one.
What if one of the systems has no API?
Then it is reachable through a browser session at best, which is more fragile and cuts the automatable share. If it is desktop-only software, the honest answer is often that this task is not worth automating.
How long does a one-way sync take to build?
Our one-workflow price is $4,500 and three weeks, and a straightforward one-way sync between two systems with real APIs sits inside that. Record matching on messy historical data is what pushes a project past it.