Unstructured Data Management Tips

Structured data, such as names and phone numbers, fits neatly into rows and columns. Unstructured data, however, has no fixed scheme, and may have a highly complex format such as audio files or web pages. 

Unfortunately, there's no single best way to effectively manage unstructured data. On the bright side, there are several approaches that can be used to successfully tackle this critical, yet persistently elusive challenge. Here are five tested ways to achieve effective unstructured data management from experts who participated in online interviews. 

Tip 1. Use AI-powered vector databases combined with retrieval-augmented generation 

"One of the most effective methods I've seen is using AI-powered vector databases combined with retrieval augmented generation," says Anbang Xu, founder of AI video generator firm Jogg.AI. A former senior software engineer at Google, Xu suggests that instead of forcing unstructured data into rigid schemas, using vector databases will allow enterprises to store and retrieve data based on contextual meaning rather than exact keyword matches. "This is especially powerful for text, audio, video, and image data, where traditional search methods fall short," he notes.  

For example, Xu says, organizations using AI-powered embeddings can organize and query vast amounts of unstructured data by meaning rather than syntax. "This is what powers advanced AI applications like intelligent search, chatbots, and recommendation systems," he explains. "At Jogg.AI, we've seen first-hand how AI-driven indexing and retrieval make it significantly easier to turn raw, unstructured data into actionable insights." 

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Read Tips 2-5 on InformationWeek.