AI has entered many aspects of data integration, including data mapping. AI data mapping involves smart identification and mapping of data from one place to another. Sometimes, creating data pipelines manually can be important. The process might require complex transformations…

Picture this: You are part of a BI team at a global garment manufacturer with dozens of factories, warehouses, and stores worldwide. Your team is tasked with extracting insights from company data.     You begin the ETL (Extract, Transform, Load) process…

The year is 1424. You’re shipping goods across the world, and the ship in question gives you a bill of lading. It’s a piece of paper containing details about what your goods are, where you’re shipping them from, and where…

Data pipeline automation plays a central role in integrating and delivering data across systems. The architecture is excellent at handling repetitive, structured tasks, such as extracting, transforming, and loading data in a steady, predictable environment, because the pipelines are built…

Remember the early 2000s, when data was difficult to make sense of? It was like an exclusive domain of a few selected IT experts. Because back then, accessing and understanding data was a monumental task, loaded with delays and complexities….