Contextual Data, Data Transformation and Measurement

The importance of data ingestion and integration for enterprise AI

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

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Enterprise Data Integration Data Quality Contextual Data

MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

OCTOBER 19, 2021

Feature stores aim to solve the challenge that many data scientists in an organization require similar data transformations and features for their work and labeling solutions deal with the very real challenges associated with hand labeling datasets. The iteration cycles should be measured in hours or days, not in months.

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Data Leaders Brief

The importance of data ingestion and integration for enterprise AI

MLOps and DevOps: Why Data Makes It Different

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