IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. It encompasses risk management and regulatory compliance and guides how AI is managed within an organization. Capture and document model metadata for report generation.

Risk 70

Risk Modeling Management Metadata 70

Octopai

JULY 12, 2020

With Octopai’s suite of metadata management tools in place, the BI team had a central location for data lineage. We now get the benefit of proliferated data quality.” – Andrew Stewardson, Data Risk Manager, FCSA. Automated Data Lineage & Discovery Provides Enterprise-Wide Benefits.

Data Warehouse 84

Data Warehouse Data Quality Metadata Risk Management 84

CIO Business Intelligence

APRIL 28, 2023

True sovereign clouds require a higher level of protection and risk management for data and metadata than a typical public cloud. Metadata, or information about the data such as IP addresses or host names, must be protected along with the data itself.

Data Processing 69

Data Processing Metadata Cost-Benefit Risk Management 69

Octopai

JUNE 16, 2021

The excessive financial risk-taking engaged in by banks on the eve of the 2007-2009 financial recession prompted new regulations to strengthen the supervision, regulation and risk management of banks. Credit Risk Management and Basel III. Operational risk management. Operational risk (i.e.

Management 52

Management Risk Management Risk Visualization 52

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. internal metadata, industry ontologies, etc.) names, locations, brands, industry codes, etc.)

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 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

AWS Big Data

AUGUST 14, 2023

How do we define “risk” and “value” in the context of data products, and how can we measure this? To answer questions such as these and plan accordingly, organizations must implement data product portfolio management (DPPM). Strategies for measuring value and prioritizing data products are explored later in this post.

Management 98

Management Risk Measurement Optimization 98

AWS Big Data

SEPTEMBER 26, 2024

The serverless nature of this architecture provides inherent benefits, including automatic scaling, seamless updates and patching, comprehensive monitoring capabilities, and robust security measures, enabling organizations to focus on innovation rather than infrastructure management.

Data Lake 115

Data Lake Cost-Benefit Unstructured Data Modeling 115

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

By measuring performance, they drive improvements through necessary process and workflow changes. And how willing are key people to move away from current data management practices and tools?”. Your dream of effectively managing an enterprise-wide master data model can be a reality. You must be able to measure your performance.

Metrics 59

Metrics Measurement Data-driven Strategy 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.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84

Alation

DECEMBER 8, 2022

At the risk of introducing yet another data governance definition, here’s how Forrester defines the term: A suite of software and services that help you create, manage, and assess the corporate policies, protocols, and measurements for data acquisition, access, and leverage. An Evaluation of Leading Use Cases.

Data Governance 52

Data Governance Data-driven Reporting Strategy 52

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.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Laminar Security

MAY 3, 2023

5: Data Security Policies and Process are Key to Using a DSPM “Security and risk management leaders have several important steps to take when reviewing the capabilities of, and deploying, DSPM technologies (see Figure 1). Don’t worry, if your organization isn’t yet creating custom policies, Laminar has you covered. . #6:

Management 40

Management Risk Risk Management Data Processing 40

Andrew White

JANUARY 11, 2021

Value Management or monetization. Risk Management (most likely within context of governance). Product Management. measuring value, prioritizing (where to start), and data literacy? Saul Judah is our main person focusing on D&A risk management. Governance. Architecture. Great idea.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

CIO Business Intelligence

MARCH 5, 2025

The EU AI Act introduces a strict legal framework with a detailed classification of AI risks and mandatory requirements for high-risk systems, which is more prescriptive than NISTs voluntary framework or the UKs principles-based approach. Emphasizes governance and risk management similar to the EU AI Act and Canadas Bill C-27.

Risk 121

Risk Risk Management Measurement Modeling 121

erwin

APRIL 21, 2020

By combining physical system catalogs, critical data elements, and key performance measures with clearly defined product and sales goals, you can manage the effectiveness of your business and ensure you understand what critical systems are for business continuity and measuring corporate performance.

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. So one of the biggest lessons we’re learning from COVID-19 is the need for data collection, management and governance.

Measurement 96

Measurement Sales Data Governance Metadata 96

IBM Big Data Hub

FEBRUARY 22, 2024

But it’s equally important that they have a deep understanding of the risks and limitations of AI and how to implement the appropriate security measures and ethics guardrails. Note: These measures of responsibility must be interpretable by AI non-experts (without “mathsplaining”).

Metadata 91

Metadata Measurement Risk Modeling 91