erwin

SEPTEMBER 17, 2020

For example, automatically importing mappings from developers’ Excel sheets, flat files, Access and ETL tools into a comprehensive mappings inventory, complete with auto generated and meaningful documentation of the mappings, is a powerful way to support overall data governance. Data quality is crucial to every organization.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

CIO Business Intelligence

MARCH 24, 2023

It must be clear to all participants and auditors how and when data-related decisions and controls were introduced into the processes. Data-related decisions, processes, and controls subject to data governance must be auditable. IBM Data Governance IBM Data Governance leverages machine learning to collect and curate data assets.

Data Governance 142

Data Governance Management Metadata Data Quality 142

erwin

JULY 12, 2019

Modern, strategic data governance , which involves both IT and the business, enables organizations to plan and document how they will discover and understand their data within context, track its physical existence and lineage, and maximize its security, quality and value. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Octopai

JULY 9, 2020

It required banks to develop a data architecture that could support risk-management tools. Not only did the banks need to implement these risk-measurement systems (which depend on metrics arriving from distinct data dictionary tools), they also needed to produce reports documenting their use.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

erwin

OCTOBER 24, 2019

Organizations are dealing with numerous data types and data sources that were never designed to work together and data infrastructures that have been cobbled together over time with disparate technologies, poor documentation and with little thought for downstream integration. With erwin, organizations can: 1.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Octopai

APRIL 8, 2020

While there are many factors that led to this event, one critical dynamic was the inadequacy of the data architectures supporting banks and their risk management systems. It required banks to maintain data architecture supporting risk aggregation at all times.

Finance 52

Finance Cost-Benefit Metadata Data Architecture 52

Cloudera

SEPTEMBER 7, 2023

Use NLP to analyze and break down regulatory documents, translating complex legal jargon into actionable tasks. AI-ify risk management. Leverage ML/AI to refine risk models, incorporating data from diverse sources, and predicting outcomes based on market sentiment, climate data, etc.

Insurance 80

Insurance Risk Data-driven Finance 80