ETL and data integration, on the same platform as your master data
Design pipelines visually, preview every transformation, push the work down to your database and schedule it all — then feed clean, matched data straight into MDM and BI.
What is ETL?
ETL — extract, transform, load — is the process of pulling data out of source systems, reshaping and cleansing it, and loading it into a target such as a data warehouse, a data lake or an MDM hub. Data integration is the broader practice of combining those sources into one consistent view. EternityArc does both, and because ETL, data quality and Master Data Management share one platform, there is no hand-off between tools where data loses its lineage.
Visual pipeline designer
Build extract, transform and load pipelines on a canvas — sources, joins, lookups, expressions, filters and targets.
Data preview
Preview the rows at any step before you run, so transformations are checked against real data.
SCD Type 2
Keep full history of slowly changing dimensions with built-in Type 2 handling.
Pushdown
Run transformations inside Snowflake, Oracle or SQL Server instead of moving the data out.
Orchestration & scheduling
Chain pipelines, MDM jobs and refreshes into scheduled, monitored workflows.
Built-in data quality
Apply validation and reject rules as data flows, not as a separate clean-up step.
End-to-end lineage
Follow a value from source through every transformation into the golden record and the dashboard.
Informatica migration
Move existing Informatica workloads across with a guided migration and advisor.
ETL and data integration questions
What is ETL?
ETL stands for extract, transform, load: data is extracted from source systems, transformed (cleansed, joined, reshaped) and loaded into a target such as a data warehouse or MDM hub.
What is the difference between ETL and ELT?
ETL transforms data before loading it; ELT loads it first and transforms it inside the target database. EternityArc supports both through pushdown, which runs transformations inside Snowflake, Oracle or SQL Server.
Which databases can EternityArc ETL read and write?
EternityArc pipelines work with Snowflake, Oracle and Microsoft SQL Server.
Does EternityArc support slowly changing dimensions?
Yes. SCD Type 2 is built in, so dimension history is kept automatically.
Why combine ETL with Master Data Management?
On one platform, data loaded by a pipeline flows straight into validation, matching and the golden record with lineage intact, instead of crossing a hand-off between separate tools.
Need one trusted record per customer or product? See Master Data Management in EternityArc.
Bring a pipeline — we'll build it with you
See source to target, with preview and lineage, on your own database.
