Slowly we are seeing a theoretical interpretation layer forming which interprets blockchain data, not only from a single chain but across multiple chains. The process is slow, since spinning up the full pipeline from indexer including processing can be tedious.

Monkey on the chain | wrangling data at The Indexing Company
https://www.indexing.co/

These complete pipelines save the engineers time, which they can spend then on higher level interpretations of the blockchain data.  

In the process of seeing data ecosystems bloom and forming shared definitions and interpretations, we will see neighborhoods form.

Where analysts and data engineers collaborate across projects to interpret the onchain activity and serve their products better. Pipelines can be copied between projects and even between neighborhoods, speeding up the time to complete analysis and UI integrations.

We already see in our systems the time to spin up ETL pipelines for onchain data can be reduced heavily. 

Once we are at a stage that this is fully self serve, the developers can quickly retrieve exactly the data they want, apply transformations and get the data in their own environments fast.