CIO Business Intelligence

MAY 2, 2023

But there are common pitfalls , such as selecting the wrong KPIs , monitoring too many metrics, or not addressing poor data quality. Consider how it looks to nontechnical executives when every digital transformation initiative has customized dashboards, different KPIs, and metrics with underlying data quality issues.

Digital Transformation 140

Digital Transformation IT Data-driven Metrics 140

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.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

IBM Big Data Hub

AUGUST 23, 2023

It is really well done, but as someone who spends all my time working on data governance and privacy, that top left section of “contextual data → data pipelines” is missing something: data governance.

Data Governance 54

Data Governance Enterprise Modeling Risk 54

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.

Enterprise 75

Enterprise Data Integration Data Quality Contextual Data 75

Ontotext

AUGUST 31, 2023

It’s also possible to import or create an ontology in a knowledge graph to model your domain without loading data, which is extremely beneficial in some use cases. Unlock the full potential of your data! Machine-interpretable: Designed to be processed, analyzed, and interpreted by humans and machines.

Modeling 64

Modeling Optimization Knowledge Discovery Enterprise 64

erwin

JULY 17, 2019

Outsourcing these data management efforts to professional services firms only delays schedules and increases costs. With automation, data quality is systemically assured. The data pipeline is seamlessly governed and operationalized to the benefit of all stakeholders. Digital Transformation Strategy: Smarter Data.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98