Analytics environment

Veracity offers a secure and scalable analytics environment through Azure Databricks, deployed within a private VNET to meet enterprise security requirements. Using Databricks Notebooks, users can develop and execute Python-based analytics workflows directly against the data lake, working with both structured datasets (tables) and raw files. Output data — whether refined datasets, analytics results, or files — can be stored and shared securely. Azure Databricks provides a unified platform for large-scale analytics, data engineering, AI, and machine learning, enabling teams to build, deploy, and maintain advanced data solutions.

Azure Databricks is a unified, open analytics platform for building, deploying, sharing and maintaining analytics and AI solutions at scale. Databricks allows you to do large scale analytics, data engineering processes, workflows, AI and machine learning. In Azure Databricks, notebook is the primary tool for creating data science and machine learning workflows.

Azure Databricks documentation

How does Databricks connect to Veracity data platform storage

A dedicated Databricks environment is enabled for a single workspace in Veracity Data Platform on request. Veracity managed Databricks environments enable Unity Catalog, a unified governance solution for data and AI assets on Databricks.

All structured data (datasets) and all files stored in the Data Workbench workspace are available in the databricks catalog and can be processed. New datasets and files can be created and synched back to Veracity Data platform.