Production-Ready and Resilient Disaster Recovery for DLT Pipelines
Disaster recovery is a standard requirement for many production systems, especially in the regulated industries. As many companies rely on data to make...
Distributed Data Governance and Isolated Environments with Unity Catalog
Effective data governance is essential for any organization that relies on data, analytics and AI for its operations. In many organizations, there is...
Finding a Data Platform that Can Do More, With Less
In today's economy, the key phrase is "do more with less." Doing more with less is not just about reducing infrastructure cost, but...
Data Vault Best practice & Implementation on the Lakehouse
In the previous article Prescriptive Guidance for Implementing a Data Vault Model on the Databricks Lakehouse Platform , we explained core concepts of...
The 3Ds of Migrating Teradata Workloads to the Databricks Lakehouse Platform
Many large enterprises have used Teradata data warehouses for years, but the storage and processing costs of on-premises infrastructure severely restricted who could...
Best practices for cross-government data sharing
Government data exchange is the practice of sharing data between different government agencies and often partners in commercial sectors. Government can share data...
Best Practices for Realtime Feature Computation on Databricks
As Machine Learning usage continues to rise across industries and applications, the sophistication of the Machine Learning pipelines is also increasing. Many of...
How To Migrate Your Oracle PL/SQL Code to Databricks Lakehouse Platform
Oracle is a well-known technology for hosting Enterprise Data Warehouse solutions. However, many customers like Optum and the U.S. Citizenship and Immigration Services...
Announcing Multi-Cloud support for Security Analysis Tool (SAT)
Last November, we announced the availability of the Security Analysis Tool (SAT) for AWS on our blog . Today we are excited to...
Announcing Support for Enhanced Fan-Out for Kinesis on Databricks
Historically, conventional wisdom held that stream processing is the domain of strictly low latency, operational use cases like sub-second inventory updates on an...