Automation Data Discovery Metadata 
IBM Journey to AI blog
OCTOBER 30, 2024
IBM watsonx™ can be used to automate the identification of regulatory obligations and map legal and regulatory requirements to a risk governance framework. The enhanced metadata supports the matching categories to internal controls and other relevant policy and governance datasets.
IBM Journey to AI blog
DECEMBER 16, 2022
An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.
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IBM Journey to AI blog
APRIL 20, 2023
This trust depends on an understanding of the data that inform risk models: where does it come from, where is it being used, and what are the ripple effects of a change? Moreover, banks must stay in compliance with industry regulations like BCBS 239, which focus on improving banks’ risk data aggregation and risk reporting capabilities.
IBM Journey to AI blog
JULY 3, 2024
Align your data strategy to a go-forward architecture, with considerations for existing technology investments, governance and autonomous management built in. Look to AI to help automate tasks such as data onboarding, data classification, organization and tagging.
IBM Journey to AI blog
JANUARY 5, 2023
Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads. Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable.
Snorkel AI
JULY 5, 2023
Generally, data is produced by one team, and then for that to be discoverable and useful for another team, it can be a daunting task for most organizations. Even larger, more established organizations struggle with data discovery and usage. But in other cases, as much as you can automate, the better you are.
Snorkel AI
JULY 5, 2023
Generally, data is produced by one team, and then for that to be discoverable and useful for another team, it can be a daunting task for most organizations. Even larger, more established organizations struggle with data discovery and usage. But in other cases, as much as you can automate, the better you are.
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