Simplifying Unstructured Data Ingestion: EPAM’s BadgerDoC Powered by Lakehouse


TYPELightning Talk

Extracting quality insights from unstructured data while maintaining lineage and governance is a unique and difficult challenge for organizations. Join EPAM for an insightful session to gain an understanding of how EPAM’s BadgerDoC effectively enhances the data ingestion pathway using Databricks Data Intelligence Platform.


Databricks facilitates the unification of structured and unstructured data via Unity Catalog, enabling convenient data onboarding through a flexible model. This allows for extraction and review of pertinent data segments and the ability to amalgamate them with other data sources seamlessly. EPAM’s BadgerDOC brings visibility and control to your data intake jobs using Databricks workflows. It allows you to glimpse transitional data and amend any issues, circumventing the need to rerun an entire ingestion pipeline.


The takeaway? BadgerDOC enables you to extract superior quality information from your unstructured data while preserving full lineage and governance as per the Unity Catalog’s capabilities. Think of BadgerDOC as a powerful window into your Lakehouse. Join the session to see that window yourself.


Jonathan Rioux

/Managing Principal, AI Consulting