Category: Databricks

Regulators expect timely, accurate disclosures; investors demand transparent ESG performance; customers reward brands that do the right thing and prove it. Yet inside most enterprises, compliance is chaotic, with internal data scattered across finance, supply chain, HR, and operations. Databricks helps break down these silos, unifying enterprise data on a single platform so organizations can…

In today’s data-driven world, businesses sit on mountains of data, but turning raw data into actionable insights remains a major challenge. Multiple siloed systems, fragmented datasets, and the sheer complexity of analysis often leave organizations paralyzed, unable to extract meaningful insights promptly. Decision-making slows, opportunities are missed, and teams are bogged down in manual data…

In today’s data-driven world, enterprises handle massive amounts of continuously arriving data from various sources. Google Sheets often serves as a quick and easy way for teams to manage and share data, especially for smaller datasets or collaborative efforts. However, when it comes to advanced analytics, larger datasets, or integration with other complex data sources,…

When working with large-scale data in Databricks Delta Lake, it’s common to create copies of tables for testing, development, or archival purposes. However, not all copies are created equal. In Delta Lake, shallow copy and deep copy serve different purposes and have very different behaviors — both in terms of performance and data isolation. In…

These days, many teams use Microsoft Fabric OneLake for unified storage and Databricks Unity Catalog (UC) for data governance and analytics. But here’s the catch: when you try to connect them directly, you hit a wall. You can’t simply register a Fabric Lakehouse as an external location in Databricks Unity Catalog like you would with…

A Data clean Room is a secure space that enables businesses to work together on sensitive data without exposing or compromising it. By using robust protocols and advanced technologies it allows multiple parties to combine and analyse information while ensuring strict adherence to privacy regulations and compliance requirements.  Let’s consider a scenario where two organizations…

Ingesting and managing data from more than 400 MySQL tables on recurring schedules is a complex challenge. Traditional approaches often lead to pipelines that are difficult to scale, hard to maintain, and prone to failure when handling schema changes or scheduling dependencies. To address these challenges, we designed and implemented a configuration-driven ingestion framework using…

Introduction In today’s fast-paced data-driven world, real-time data processing and change data capture (CDC) are crucial for businesses to make timely and informed decisions. Databricks, a powerful cloud-based analytics platform, combined with Debezium, an open-source CDC tool, enables seamless real-time data replication and transformation. This blog will explore Databricks and Debezium, detailing their integration and…