How it works
Incremental Loads

Not so long ago a nightly data warehouse update of transational data created from the previous day was actually good enough. Reports using data from the day or even week prior were considered satisfactory and the idea of running extracts from a source system of millions of rows during working hours was not even considered.

Today, the demand for real-time or near real-time updates is the new normal. To meet this demand, the data onboarding process needs to ensure minimal impact on the source system and needs to be as seamless as possible.

Loome natively provides the capability to set "incremental" loads from source system to target without writing a line of code. Loading data incrementally allows you to identify and define the extact time and sequence of events. If you require intra-day updates, whether it be in the last hour or even last minute, Loome tasks can be configured to only onboard the data within the specified time frame, reducing performance impact on the source, and ensuring the target is as up to date as needed.

Change Auditing

Persistent Staging is an advanced data migration that tracks changes to source records over time. This means with each persistent staging migration, when data is changed or modified in the source, Loome will retain both a record of the data as it was at the time of the prior migrations, and insert the data in its current state.

A gif showing how Loome Integrate user can manage incremental logic and change auditing.
Find out More
Read more about change auditing and what you can do right now to ensure better data quality and governance in your analytics ecosystem.