Allowing quality data in can lead to a better understanding of an organization. Here are 5 steps to improve your organization's data quality for unstructured data. Image: momius/Adobe Stock ...

What unstructured data means for data management The differences between structured and unstructured data mean that traditional database systems and modern AI database systems handle information ...

While structured data is typically numbers and other values, unstructured data is more complex and comes in the form of video files, IoT sensor data, and other examples.

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.

This is a significant departure from the traditional ETL world where a single vendor could extract and transform the structured or semi-structured data because the traditional ETL process is a linear ...

Being “ready for AI” is a commitment to continuously refining how your organization collects, manages and mobilizes data.

Big Data refers to massive volumes of structured and unstructured data that are too large or complex for traditional data processing tools. It's not just about size — it's also about the insights that ...

The problem with unstructured data is that it keeps on growing. Today’s distributed file systems and cloud object stores have practically unlimited storage capacities. It’s so easy to spin up another ...

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

Big data can come in various formats, such as structured, unstructured, text, images, sound, video, etc. This diversity makes it challenging yet rewarding to analyze.

The use of unstructured data in GenAI introduces new types of governance, privacy and security risks that these traditional data management tools aren’t equipped to handle. To safely leverage ...