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 Finding ...

Several factors, like consistency, accuracy, and validity, contribute to data quality. When left unchecked, businesses that utilize inconsistent, inaccurate, or invalidated data can lead to poor ...

Google’s Lang Extract uses prompts with Gemini or GPT, works locally or in the cloud, and helps you ship reliable, traceable data faster.

Enterprise AI is only as good as the data that is available to a model. In the past, enterprises largely relied on structured data. With the rapid adoption of generative AI, enterprises are ...

Most enterprise data lives outside databases. Here's why that's holding AI back — and how connecting context can change it.

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data ...

Unstructured data isn’t an asset by default — it’s a liability until CIOs govern, lifecycle and curate it for AI-ready value.

Large language models (LLMs) such as OpenAI’s GPT-4 are the building blocks for an increasing number of AI applications. But some enterprises have been reluctant to adopt them, owing to their ...

Ataccama ONE and Precisely Trillium are two data quality tools that promise to streamline the data cleaning process. Decide which one is right for you. Image: NicoElNino/Adobe Stock Ataccama ONE and ...

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