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

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

When storing big data, data lakes and data warehouses have different features. Data warehouses store traditional transactional databases and store data in one table with structured columns.

Data Loss During Conversion: When converting unstructured or semi-structured data into structured formats, valuable context or details may be lost.

In the ever-evolving landscape of data management, two key concepts have emerged as essential components for organizations seeking to harness the power of their data: data marts and data lakes. While ...

Data Science: An interdisciplinary field, data science relies on scientific methods, processes, algorithms, and systems to extract or extrapolate knowledge and insights from structured and ...

The AI then begins to draw inferences based on this. AI relies heavily on complex statistical algorithms developed by data scientists to interrogate an array of both structured and unstructured data.

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