Contextual Data Data Quality Risk 
CIO Business Intelligence
MAY 2, 2023
The risk of derailments increases as I hear inconsistent answers or too many conflicting priorities. But there are common pitfalls , such as selecting the wrong KPIs , monitoring too many metrics, or not addressing poor data quality. The five derailments I focus on here fall within the CIO’s responsibilities to address.
erwin
JULY 17, 2019
EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. Outsourcing these data management efforts to professional services firms only delays schedules and increases costs. With automation, data quality is systemically assured.
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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.
IBM Big Data Hub
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.
IBM Big Data Hub
AUGUST 23, 2023
This data governance requires us to understand the origin, sensitivity, and lifecycle of all the data that we use. It is the foundation for any AI Governance practice and is crucial in mitigating a number of enterprise risks. The problem is that these use cases require training LLMs on sensitive proprietary data.
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