IBM Big Data Hub

OCTOBER 4, 2022

This includes capturing of the metadata, tracking provenance and documenting the model lifecycle. The ability to track and share model facts and documentation across the organization provides backup for analytic decisions. Having this backup is crucial when addressing stakeholder, customers and concerns from regulators.

Metadata 97

Metadata Risk Management Risk Experimentation 97

erwin

OCTOBER 31, 2019

While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

erwin

FEBRUARY 4, 2021

While acknowledging that data governance is about more than risk management and regulatory compliance may indicate that companies are more confident in their data, the data governance practice is nonetheless growing in complexity because of more: Data to handle, much of it unstructured.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

erwin

APRIL 2, 2021

While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, management and governance issues that must be addressed. From risk management and regulatory compliance to innovation and digital transformation, you need data intelligence.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

Octopai

JULY 9, 2020

By adopting automated data lineage and automated metadata tagging, companies have the opportunity to increase their data processing speed. That increase can manage huge endeavors, such as migrations, error location, and new data governance integrations which then become “routine” operations.

Insurance 98

Insurance Risk Management Machine Learning Metadata 98

IBM Big Data Hub

FEBRUARY 8, 2024

” European Parliament News The EU AI Act in brief The primary focus of the EU AI Act is to strengthen regulatory compliance in the areas of risk management, data protection, quality management systems, transparency, human oversight, accuracy, robustness and cyber security.

Risk Management 72

Risk Management Risk Machine Learning Metrics 72

erwin

NOVEMBER 13, 2020

Data Security & Risk Management. Innovation Management. For example, a COVID response plan will use EA to document if employees work from home, what their roles are, the projects on which they’re working, and what their schedules are. Digital Transformation. Compliance/Legislation. Artificial Intelligence.

Enterprise 131

Enterprise Digital Transformation Key Performance Indicator Data-driven 131

erwin

APRIL 21, 2020

Another foundational purpose of a data catalog is to streamline, organize and process the thousands, if not millions, of an organization’s data assets to help consumers/users search for specific datasets and understand metadata , ownership, data lineage and usage. Clearly Document Data Policies and Rules. See a Data Catalog in Action.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

As COVID-19 continues to spread, organizations are evaluating and adjusting their operations in terms of both risk management and business continuity. One example is the European Union (EU) Open Data Portal , which is used to document, catalog and govern EU data related to the pandemic. Clearly Document Data Policies and Rules.

Measurement 96

Measurement Sales Data Governance Metadata 96

IBM Big Data Hub

OCTOBER 16, 2023

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Capture and document model metadata for report generation.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

SEPTEMBER 26, 2024

Organizations are collecting and storing vast amounts of structured and unstructured data like reports, whitepapers, and research documents. End-users often struggle to find relevant information buried within extensive documents housed in data lakes, leading to inefficiencies and missed opportunities.

Data Lake 98

Data Lake Cost-Benefit Unstructured Data Modeling 98

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States. To reference SR 11-7: .

Risk 64

Risk Modeling Machine Learning Data Quality 64

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. Inaccurate Data Management Leads to Financial Collapse. These tools extract, sort, and integrate thousands of metrics.

Finance 52

Finance Cost-Benefit Metadata Data Architecture 52

Alation

MARCH 14, 2023

All critical data elements (CDEs) should be collated and inventoried with relevant metadata, then classified into relevant categories and curated as we further define below. Store Where individual departments have their own databases for metadata management, data will be siloed, meaning it can’t be shared and used business-wide.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

IBM Big Data Hub

FEBRUARY 8, 2023

Documented, explainable model facts are necessary when defending analytic decisions. An AI Governance solution driving responsible, transparent and explainable AI workflows The right AI governance solution can help to better direct, manage and monitory your organization’s AI activities.

Risk Management 52

Risk Management Risk Metadata Modeling 52

IBM Big Data Hub

SEPTEMBER 20, 2022

Often data scientists aren’t thrilled with the prospect of generating all the documentation necessary to meet ethical and regulatory standards. This is where technology such as IBM FactSheets , can help by reducing the manual labor needed to capture metadata and other facts about a model across stages of the AI lifecycle.

Metadata 56

Metadata Machine Learning Data-driven Risk 56

erwin

DECEMBER 20, 2018

Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. Its value can be hard to demonstrate to those who don’t work directly with data and metadata on a daily basis.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for Allows metadata repositories to share and exchange.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84

Ontotext

FEBRUARY 26, 2024

Risk management : Understanding the correlation between events and stock price fluctuations helps manage risk. Quality assurance process, covering gold standard creation , extraction quality monitoring, measurement, and reporting via Ontotext Metadata Studio. Let’s have a quick look under the bonnet.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Alation

OCTOBER 26, 2021

They enjoy improved governance, which follows from documenting ownership of business terms and formulas. And, by implementing continuous data reviews, finance teams better support compliance and risk management. They can add metadata in the business glossary to indicate what types of compliance reporting a term supports.

Finance 52

Finance Data Transformation Enterprise Metrics 52

Grooper

OCTOBER 23, 2019

Responsibility for managing your company’s data must be clearly defined and supported. For example, business growth, profits, cost and performance optimization, efficiency, compliance, and risk management. How will you show that information management improvements directly affect overall organizational performance?

Metrics 59

Metrics Measurement Strategy Data-driven 59

IBM Big Data Hub

FEBRUARY 22, 2024

The method merges best practices in data science, project management, design frameworks and AI governance. Teams can easily see and understand the requirements at each stage of the lifecycle, including documentation, who they need to talk to or collaborate with, and next steps. Provide content grounding for AI models.

Metadata 91

Metadata Measurement Risk Modeling 91

AWS Big Data

AUGUST 14, 2023

These may be data products consumed in the implementation of key business activities, or associated with critical processes such as regulatory reporting and risk management. Its implementation may be adapted from or managed by existing demand management processes within the organization.

Management 83

Management Risk Measurement Optimization 83