“Data pipeline” and “Extract, Transform, Load” (ETL) are common phrases encountered in just about every data integration. But what’s the difference?

The point of evidence is to guide decisions, so transforming a business into being evidence-based has to start with leaders.

Good data hygiene means data is correct and easily used to draw insight. This definition then begs the question: How do you achieve it?

Backcountry, the specialty retailer of premium outdoor gear and apparel, shares key lessons on using a modern data stack to overcome data silos, complexities with legacy systems and improve its customer experience.

Leading fintech companies AJ Bell, OrderPay and Tide are blazing a path toward better insights with a new, modern approach to data: self-service analytics.

Is your data warehouse modern enough? Learn the differences, benefits and available tools and strategies for easy migration.

From cost-effectiveness to what adds business value — what Autodesk considers critical when deciding whether to buy versus build data pipelines.

Change data capture (CDC) identifies and captures data changes in source systems. Here’s a list of the best CDC tools.

A data warehouse is a centralized storage system for structured data. The data stored here is used for reporting, analytical processing and business intelligence.

A distributed database can offer benefits and tools to any company’s data storage and analytics processes — as long as they know how to use one.