BI to AI Agents: The Next Evolution of Enterprise Data Platforms
Enterprise data platforms are evolving beyond dashboards into AI-powered copilots that help teams understand context, surface insights, and make faster decisions.
Is Your Data Lake Quantum-Safe?
Quantum computing will shatter the cryptographic foundations of today’s digital systems. Algorithms like RSA and ECC, which protect most data lakes, VPNs, TLS communications, and disk encryptions, are vulnerable to Shor’s algorithm on a fault-tolerant quantum computer.
Breaking Cloud Boundaries: A Terraform Story of Databricks Migration Azure -> AWS
This blog post outlines a Proof of Concept (PoC) for migrating Databricks resources from Azure to AWS using Terraform. While still requiring some manual adjustments, this approach simplifies much of the resource migration using the experimental exporter from the Terraform Databricks Provider.
Hands-on practice for joining multiple SCD2 tables to make consolidated SCD2 in Data Warehousing
Joining multiple SCD2 tables effectively is fundamental to maintaining a comprehensive and accurate view of historical data.
Data Lake Orchestration: A robust and scalable approach
When we design an orchestration to build and populate Data Lake, It is highly recommended to build robust and scalable pipelines for the further possibility of growing & a variety of data, sources, and analytics needs.
Common Mistakes in DBT That Can Lead to Performance and Operational Issues
DBT (Data Build Tool) is a powerful framework for data transformation, but like any powerful tool, small missteps can lead to big issues — especially at scale. In this post, I’ll walk you through three common pitfalls I’ve seen in production DBT projects that can cause performance degradation, operational issues, or incorrect lineage tracking — and how to avoid them.