Unstructured data is created at an incredible rate each day and with the advent of artificial intelligence and machine learning tools to gather, process, analyze and report insights from ...

Unstructured data is complicated compared to working with structured data - Finding the insight buried within unstructured data is challenging. It requires a high level of technical and analytics ...

Unlike structured data, which fits neatly into rows and columns in a database, unstructured data is usually in its raw form, often comprising text, images, audio, or video.

IT pros have different priorities for structured data versus unstructured data (Source: Igneous’ “2018 State of Unstructured Data Management Report”) In addition, respondents ranked “automating data ...

This step involves using OpenAI technology to process the unstructured data and convert it into structured data. Next, you’ll need to provide the model name GPT-3.5 Turbo .

Implementing AI in healthcare isn’t just about choosing the right tools—it’s about making them work in the real world.

Organizations can tap into their unstructured data by working with it in its native form. Just because unstructured data doesn’t fit in an Excel sheet, doesn’t mean it’s impossible to work with.

Unstructured data — information that doesn’t follow conventional models or fit into structured database formats — represents more than 80% of all new enterprise data.

Today at AWS re:invent 2024 the company announced a series of new services and updates designed to help make it easier for enterprises to get both structured and unstructured data into RAG pipelines.

However, structured data, such as a CRM database or data stored in proprietary software, can be much more complicated and can derail the e-discovery process if not managed carefully.