What is data integration?

Data integration brings information from different systems together into a usable, consistent view. It enables people to analyze and plan across sources that would otherwise remain separate.

A distributor may hold sales and stock in an ERP, customer activity in a CRM and financial plans in another system. Integration connects the relevant data so teams can ask questions across those boundaries. Combining files alone is not enough: identifiers, definitions and update timing must also make business sense.

Start by identifying the source data and the business questions it must support. Connect to the sources using supported methods, map related fields and prepare the data for its destination. Validate the results, agree a refresh schedule and monitor the ongoing connection.

For example, a customer may have different identifiers in an ERP and a CRM. The integration needs an agreed way to match those records so sales and account activity are not attributed to the wrong customer. Record the mapping rules so they can be checked when the source changes.

Data integration describes the broader goal and process. Extract, transform, load (ETL) is one approach to moving and preparing data. An application programming interface (API) provides a defined way for software to communicate. A connector enables access or transfer using a supported method.

Data blending usually refers to combining datasets for analysis. Data quality concerns whether the resulting information is fit for its purpose. These concepts support integration, but they are not interchangeable names for it.

No. Integration and refresh frequency are separate questions. A connection may refresh on a schedule rather than processing every change immediately. Readers need to know when the data was last updated and which source it represents.

For inventory decisions, a recent sales view can still differ from the live ERP position if new orders or receipts have arrived since the last refresh. Use the actual configured cadence and business process when describing freshness. Do not treat “connected,” “live” and “streaming” as interchangeable promises.

A shared view can help sales, purchasing and finance work from consistent customer, product and performance information. It also gives teams a place to investigate a result instead of reconciling separate extracts for every question. The benefit depends on clear definitions, appropriate access and reliable source data.

Phocas connects business data for analysis, reporting and planning. The supported source systems, access methods and refresh schedule depend on the integration and business requirements.