A recurring theme in big data over the past two decades is the poor quality of data. No matter how much ink is spilled on the topic, organizations continually seem surprised that the data they want to ...

AI and data are feeding each other — build the right strategy and you’ll unlock smarter decisions, better agility and a real ...

The enterprise data landscape is undergoing a fundamental shift as the importance of unstructured data grows in parallel with the rise of generative AI and agentic workflows. Data platforms are ...

Shenzhen Tianyu Smart Technology Co., Ltd. applied for a patent titled "A Method for Constructing Customer Profiles Based on Big Data Collection" in July 2025. This patent aims to achieve closed-loop ...

Data mapping, transformation tools, data capture, data profiling, and data quality are essential components of data integration. Data governance, workforce training and certifications, and cloud ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. We’re just starting to tap the potential of what AI can do. But amid all the breakthroughs, ...

Learn the definition of data quality and discover best practices for maintaining accurate and reliable data. Data quality refers to the reliability, accuracy, consistency, and validity of your data.

It has been estimated by MITSloan that the cumulative cost of inaccurate data is 15 to 25 per cent of revenue for most organisations. This is because poor quality data wastes resources, undermines ...