How to use end-to-end data lineage to drive better actions
Seems like everyone is talking about data lineage these days, and for a good reason. Data lineage helps ensure better data quality across your modern data stack.
But not everyone speaks the same lineage language.
Data engineers use lineage for impact and root cause analysis. Analysts and Analytics engineers use lineage to trace jobs and transformations in their warehouses. And consumers use lineage to understand why data never reached their expected destination.
This results in a narrow, siloed view lineage in which only one group benefits.
It’s time to stop using siloed lineage views for pretty graphs and start using end-to-end lineage to drive focused actions.
In the talk, you will learn:
- How data quality tailors to specific needs of data engineers, analysts, & consumers
- How data lineage should drive actions vs pretty graphs
- A real-world example of end-to-end data lineage with Airflow, dbt, Spark, and Redshift