erwin

SEPTEMBER 3, 2020

It documents your data assets from end to end for business understanding and clear data lineage with traceability. Data governance and EA also provide many of the same benefits of enterprise architecture or business process modeling projects: reducing risk, optimizing operations, and increasing the use of trusted data.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

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. Five Steps to GDPR/CCPA Compliance. Strengthen data security.

Data Governance 110

Data Governance Management Metadata Risk Management 110

erwin

APRIL 2, 2021

With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Lack of a solid data governance foundation increases the risk of data-security incidents. Data Security Starts with Data Governance.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

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. So being prepared means you can minimize your risk exposure and the damage to your reputation.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

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

erwin

APRIL 29, 2020

An understanding of the data’s origins and history helps answer questions about the origin of data in a Key Performance Indicator (KPI) reports, including: How the report tables and columns are defined in the metadata? Business terms and data policies should be implemented through standardized and documented business rules.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

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

IBM Big Data Hub

FEBRUARY 8, 2023

There is a growing need to proactively drive responsible, fair, and ethical decisions, designed to: Manage risk and reputation No organization wants to be in the news for the wrong reasons, and recently there have been a lot of stories in the press regarding issues of unfair, unexplainable, or biased AI.

Risk Management 52

Risk Management Risk Modeling Metadata 52

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 86

Insurance Risk Management Machine Learning Metadata 86

Ontotext

FEBRUARY 26, 2024

The answers to these foundational questions help you uncover opportunities and detect risks. We bundle these events under the collective term “Risk and Opportunity Events” This post is part of Ontotext’s AI-in-Action initiative aimed to empower data, scientists, architects and engineers to leverage LLMs and other AI models.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

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. Inaccurate Data Management Leads to Financial Collapse. Download the Whitepaper.

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

SEPTEMBER 20, 2022

Alongside the significant brand reputation risk, there’s also a growing set of data and AI regulations across the world and across industries — like the upcoming European Union AI Act — that companies must adhere to. Your model risk management team, IT operations team and line-of-business employees also need appropriate access.

Metadata 56

Metadata Machine Learning Data-driven Modeling 56

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

Alation

OCTOBER 26, 2021

They need trusted data to drive reliable reporting, decision-making, and risk reduction. Consistent, reliable reporting can then drive more positive outcomes for the entire business, including improved compliance, risk reduction, and increased revenue. “We This is because accurate data is “table stakes” for finance teams.

Finance 52

Finance Data Transformation Enterprise Metrics 52

AWS Big Data

AUGUST 14, 2023

At the same time, unstructured approaches to data mesh management that don’t have a vision for what types of products should exist and how to ensure they are developed are at high risk of creating the same effect through simple neglect. How do we define “risk” and “value” in the context of data products, and how can we measure this?

Management 79

Management Risk Measurement Optimization 79

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

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. We track distinct metrics for product quality, financial health, and risk, and tie this information to business value.

Metrics 59

Metrics Measurement Strategy Optimization 59

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.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84