For years, enterprise companies have been plagued by data silos separating transactional systems from analytical tools—a divide that has hampered AI applications, slowed real-time decision-making, and ...

Enterprise data warehouses, or EDWs, are unified databases for all historical data across an enterprise, optimized for analytics. These days, organizations implementing data warehouses often consider ...

Let's kick off 2024 by checking in with the current status of some of Microsoft's more popular database options, like Azure SQL Database, Azure Managed Instance and more. Happy New Year's to my ...

In fact, Microsoft has published DataOps for the modern data warehouse guidance and a GitHub repo featuring DataOps for the Modern Data Warehouse as part of its Azure Samples offerings. [Click on ...

We recently looked at the idea of the data lake, so now it’s time to head downstream and look at data warehouses. We’ll define data warehouses, look at the data types they comprise, the storage they ...

Principal Architect Sandeep Patil’s landmark research charts a new course for cloud-native data warehousing — from serverless MPP engines and lakehouse convergence to AI-powered query optimization and ...

Microsoft launched its Azure Database for MySQL and PostgreSQL services to general availability (GA) in 2018. When those services began their preview the year before, the notion that Microsoft itself ...

The "data" part of the terms "data lake," "data warehouse," and "database" is easy enough to understand. Data are everywhere, and the bits need to be kept somewhere. But should they be stored in a ...