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How textual search works in graph databases

A database, especially one full of long strings of unstructured text, is only as valuable as how easily you can search it and extract meaningful interpretations. That’s harder than ever with recent changes in how many organizations ask their teams to manage and learn from the data their functional area produces. Instead of waiting for Read the full article…

How to Build and Manage Your Own Enterprise Knowledge Graph

It’s no secret that the most successful organizations today are using enterprise knowledge graphs to achieve long-term success – whether that’s advancing a particular mission, growing the bottom line, or both. Enterprise knowledge graphs break down silos, disperse tribal knowledge, and increase collaboration. They’re also the key to retaining institutional expertise long after key employees Read the full article…

Why Robust Change Data Capture Is Essential for Knowledge Graphs

Your enterprise knowledge graph is your view of the world. It supplies all of the who, what, when, where, and why details that your organization needs for day-to-day operations and decision-making. Equally, if not more, important is that your knowledge graph is the world for your artificial intelligence. Your AI solution only knows and understands Read the full article…

Text is nothing more than unstructured data. When you consider how much textual data your enterprise organization has – or has access to – it’s no surprise that 90% of your data isn’t analyzed. Traditional analytics can only analyze structured data. But no matter how much information your organization has stored in tables, rows, and Read the full article…

Like all other categories of capital investment — machinery, plants, patented technology, unique processes — we should be investing in data to produce an asset with an expected return. But this isn’t how it works much of the time. Instead, companies invest to connect disparate systems. The “return” comes in the form of a data Read the full article…