IBM Big Data Hub
OCTOBER 16, 2023
It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.
Collibra
JUNE 2, 2022
Since AI relies heavily on data, the integrity and quality of the underlying data upon which AI models are trained is critical to ensure accuracy and remove the risk of model bias and opacity. Training data can fast become a problem without proper controls in place.
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IBM Big Data Hub
SEPTEMBER 20, 2022
Do you understand bias that exists in the data, and do you have the right guardrails to use that data for building and training models? Automated, integrated data science tools help build, deploy, and monitor AI models. It’s not just about granting proper access to data science teams.
Info Source
JUNE 5, 2019
Nuxeo AI Enables Enterprises to Easily Leverage their own Data Sets to Create, Train, and Deploy Custom AI Models. Business-specific metadata is the foundat ion of effective search, workflow, and other value-creation activities in content-centric business applications.
erwin
APRIL 15, 2020
On a business level, decisions based on bad external data may have the potential to cause business failures. In business, data is the food that feeds the body or enterprise. Better data makes the body stronger and provides a foundation for the use of analytics and data science tools to reduce errors in decision-making.
Collibra
AUGUST 14, 2023
It should clearly define the problem that the AI model solves, the data used to train the model, the desired outcomes, and the personas involved. To do so, you’ll need to collect and assess the data that’s available. You’ll want to assess whether it’s high-quality data or not. Now, it’s time to start training your model.
Collibra
FEBRUARY 16, 2022
Lastly, once the data governance framework is laid out, the committee will turn to technology and choose a platform that best supports the vision. A good technology solution will gather metadata from a variety of systems, manage a business glossary, enforce policies and procedures, tie to a technical data dictionary, and more.
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