Data integration is the work of getting separate systems to share their data so everyone is looking at the same, current picture. Your webshop knows about orders, your CRM knows about customers, your accounting tool knows about invoices. Integration links them so a change in one shows up in the others, instead of each living in its own silo with its own slightly different truth.
Picture a company where every department keeps its own private address book. Sales updates a customer’s phone number, but support, billing and delivery never hear about it, so half the company keeps calling the old number. Data integration replaces those private books with a shared one: update it once and everyone sees the change. The actual linking usually runs through an API integration between the systems, with data mapping lining up the fields so a ‘customer name’ in one tool matches the right field in another.
Done well, integration kills double entry and the errors that come with it. Done poorly, it spreads bad data faster than ever. That is why moving data is often paired with cleaning and reshaping it, the work that tools like ETL automation handle, so what flows between systems is correct as well as connected. The question that decides the whole design is a quiet one: which system is the source of truth for each piece of data? If your shop and your CRM both think they own the customer’s email, and both can change it, you will eventually get two different emails fighting each other on every sync. Good integration names one owner per field up front. Everyone else reads from it. Get that decision right and the rest is plumbing. Skip it, and you build a machine that spreads disagreement at the speed of a webhook.
At TopDevs we connect a client’s scattered tools into one consistent flow, so their teams make decisions on the same numbers instead of arguing about whose spreadsheet is right.
