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Data governance in the age of generative AI

AWS Big Data

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

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5 Data Governance Mistakes to Avoid

Alation

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029.

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Of Muffins and Machine Learning Models

Cloudera

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. In this article, we explore model governance, a function of ML Operations (MLOps). Machine Learning Model Lineage. Machine Learning Model Visibility . Machine Learning Model Explainability .

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5 Data Governance Mistakes to Avoid

Alation

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029.

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5 Ways Data Engineers Can Support Data Governance

Alation

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. How can data engineers address these challenges directly?

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Introducing Native Connector for Google BigQuery: Boosting Data Lineage, Migration, and Discovery

Octopai

This new native integration enhances our data lineage solution by providing seamless integration with one of the most powerful cloud-based data warehouses, benefiting data teams and enabling support for a broader range of data lineage, discovery, and catalog.

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Gartner Data & Analytics London: Human Curation + Machine Learning

Alation

Human Curation + Machine Learning. The way Herschel, Fry, and Zimmerman talked about AI in many respects reflects our vision for machine learning data catalogs. What’s more, Zaidi and Gartner believe that this vision of a machine-learning-enabled data catalog creates real value for enterprises.