AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Synthesizing tables—creating artificial datasets that closely resemble real ones—plays a crucial role in supervised machine learning (ML), with a wide range of practical applications. These include ...

Here's how you can use SQL Server's OpenJson function to dismantle JSON structures into relational tables targeting either transactional systems or data warehouses. JSON is great for moving data ...

Relational tables often describe more than one type of real world entity. In this tip, Bob Watkins covers some things to think about when designing such tables. In an earlier tip, I showed a way to ...

Excel used to be the poor schmuck’s database, with spreadsheets that just sort of sat there. You could create something more sophisticated with LOOKUP functions, but they were a huge hassle to set up.

When object-oriented programming languages began to be used in enterprise applications, designers had problems fitting the object-oriented model with the relational model. In the object-oriented model ...

When it comes to providing reliable, flexible, and efficient object persistence for software systems, today's designers and architects are faced with many choices. From the technological perspective, ...

In the quest to teach software to understand language, scientists have mainly focused on text as a source of data to help train their algorithms. Among other things, text is used to populate a ...