Harder to Query: Unlike structured data, which can be easily queried in databases, unstructured data requires specialized query systems or AI models to retrieve specific information.

The differences between structured and unstructured data mean that traditional database systems and modern AI database systems handle information in different ways.

We look at alternatives to relational databases that have emerged to help bring some structure to unstructured data and gain valuable insight by making it semi-structured.

In the dynamic world of data science, the conversion of unstructured data into structured data is a key process. This transformation is crucial for enabling more efficient data analysis and ...

Applying gen AI to solve useful problems at scale requires a paradigm shift in how we think about data management and integration. Krishna Subramanian, COO and co-founder of Komprise, walks through ...

Parker Harris The Data Cloud has rightly been one of Salesforce’s biggest product focuses this year. As the company’s World Tour series of events hit New York yesterday, the latest news was that it ...

Allowing quality data in can lead to a better understanding of an organization. Read more to improve your data quality for unstructured data.

Let's start by examining those two broad-brush data categories: structured and unstructured. Structured data refers to the data resident within relational databases, often presented via customer ...

Discover best practices that allow data pipelines to scale and support both structured and unstructured data.

With its latest release, Monte Carlo becomes the first data + AI observability platform to close this gap, providing AI-powered support for monitoring both structured and unstructured data types.