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. With that in mind, we’ve compiled a list of the very best, best-practice blog posts from the erwin Experts in 2018.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

erwin

SEPTEMBER 17, 2020

For example, capital markets trading firms must implement data lineage to support risk management, data governance and reporting for various regulations such as the Basel Committee on Banking Supervision’s standard number 239 (BCBS 239) and Markets in Financial Instruments Directive (MiFID II).

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? Who are the data owners? What are the transformation rules? Data Governance. The post What is Data Lineage?

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

Cloudera

JUNE 29, 2023

Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs. However, because most institutions lack a modern data architecture , they struggle to manage, integrate and analyze financial data at pace.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

erwin

SEPTEMBER 3, 2020

Documenting data in motion looks at how data flows between source and target systems and not just the data flows themselves but also how those data flows are structured in terms of metadata. We have to document how our systems interact, including the logical and physical data assets that flow into, out of and between them.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

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 Metadata Risk 106

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 4, 2019

In this blog, we will touch on these issues as well as how we can expand the scope and depth of a data governance framework. In most cases, a new data governance framework requires people – those in IT and across the business, including risk management and information security – to change how they work.

Data Governance 75

Data Governance Data Quality Risk Management Data-driven 75

erwin

NOVEMBER 13, 2020

Data Security & Risk Management. Innovation Management. Business-driven applications also will be deployed through the EA repositories, which contain a wealth of information, such as strategies, processes, peoples and skills, locations, working practices, metadata, applications and technologies. Cloud Migration.

Enterprise 131

Enterprise Digital Transformation Key Performance Indicator Data-driven 131

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

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

IBM Big Data Hub

MAY 9, 2023

This solution is designed to include everything needed to develop a consistent transparent model management process. The resulting automation drives scalability and accountability by capturing model development time and metadata, offering post-deployment model monitoring, and allowing for customized workflows.

Metadata 71

Metadata Risk Experimentation Dashboards 71

IBM Big Data Hub

APRIL 20, 2023

This level of visibility also helps ensure that changes made over time don’t introduce new risks into the organization, can make it easier for banks to stay within regulatory guidelines, and helps ensure banks can respond quickly to changing business needs.

Risk 68

Risk Risk Management Reporting Metadata 68

IBM Big Data Hub

DECEMBER 4, 2023

Its toolkit automates risk management, monitors models for bias and drift, captures model metadata and facilitates collaborative, organization-wide compliance. The post A look into IBM’s AI ethics governance framework appeared first on IBM Blog. It helps accelerate responsible, transparent and explainable AI workflows.

Consulting 74

Consulting Risk Metadata Risk Management 74

erwin

OCTOBER 3, 2019

But to mature the practice, organizations should implement an EA tool with a shared, centralized metadata repository and role-based access. Those include support for industry standard frameworks and notation, the ability to perform impact analysis and the streamlining of systems and applications.

Enterprise 111

Enterprise Cost-Benefit Data-driven Risk 111

Alation

JUNE 14, 2021

Do we know the business outcomes tied to data risk management? To support data security, an effective data catalog should have features, like a business glossary, wiki-like articles, and metadata management. Subscribe to Alation's Blog. What am I required to do? What do we know? They drive labeling.

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Metadata 97

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

Automate the capture of model metadata and increase predictive accuracy to identify how AI is used and where models need to be reworked. Risk management Automate model facts and workflows for compliance to business standards. identify, manage, monitory and report on risk and compliance at scale.

Risk Management 52

Risk Management Risk Metadata Modeling 52

IBM Big Data Hub

SEPTEMBER 20, 2022

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. Your model risk management team, IT operations team and line-of-business employees also need appropriate access.

Metadata 56

Metadata Machine Learning Data-driven Data Science 56

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.

Risk 64

Risk Modeling Machine Learning Data Quality 64

Ontotext

APRIL 21, 2021

The problem was the left hand had no way of knowing the systemic issues around data governance, risk management and compliance framework. Through rich metadata and automated reasoning , it is possible to express the complexity of assets and their relationships. Conclusion.

Metadata 59

Metadata Finance Cost-Benefit Data Quality 59

Octopai

FEBRUARY 21, 2022

But since lucky stars are generally frowned upon as a risk management strategy, we highly recommend you plan out your cloud migration process. An automated data catalog will not only self-create but will also self-update, routinely reviewing all metadata within your data landscape and updating your data catalog accordingly.

Recreation/Entertainment 98

Recreation/Entertainment Cost-Benefit ROI Reporting 98

Alation

NOVEMBER 30, 2021

This means data protection and risk mitigation must be promoted and consolidated with other enterprise risk management processes. The first step is recognizing the direct relationship between data governance and risk. All three risk functions should be aligned. Manage by Policy and Contractual Agreements.

Data Governance 52

Data Governance Risk Management Risk Enterprise 52

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. Subscribe to Alation's Blog.

Data Governance 52

Data Governance Data-driven Reporting Strategy 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

Ontotext

MAY 5, 2023

Another capability of knowledge graphs that contributes to improved search and discoverability is that they can integrate and index multiple forms of data and associated metadata. This makes it easier to manage and update information as the industry changes.

Data Collection 64

Data Collection Risk Data-driven Interactive 64

Alation

FEBRUARY 8, 2022

In our first blog in this series , we define the terms data fabric and data mesh. The second blog took a deeper dive into data fabric, examining its key pillars and the role of the data catalog in each. In this blog, we’ll do the same with data mesh, unpacking the four key pillars, with a few notes on the role of the data catalog.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 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

Alation

OCTOBER 26, 2021

And, by implementing continuous data reviews, finance teams better support compliance and risk management. Analyst productivity: With Alation, finance teams gain an end-to-end data management perspective. .” — Senior Systems Analyst at a Major Pharmaceutical Company. Subscribe to Alation's Blog.

Finance 52

Finance Data Transformation Enterprise Metrics 52

Cloudera

JANUARY 22, 2019

Cloudera enables high-value analytical use cases from the edge to AI including proactive and predictive maintenance, usage-based analytics for targeted communications, recommendation engines, Enterprise Risk Management, AML (Anti-Money Laundering), Fraud Detection/Prevention, Cybersecurity, and Machine Models.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Laminar Security

NOVEMBER 16, 2023

To learn more about the differences between DSPM and CSPM, check out our blog post on DSPM vs CSPM , and why you need both for comprehensive cloud security. While SIEM helps you collect and analyze security data from various sources, DSPM’s byproduct (metadata) helps you to further analyze security info from your cloud data.

Risk 59

Risk Cost-Benefit Dashboards Management 59

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.

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. Data is critical to these decisions, such as how to ramp up and support remote employees, re-engineer processes, change entire business models, and adjust supply chains.

Measurement 96

Measurement Sales Data Governance Metadata 96

IBM Big Data Hub

FEBRUARY 22, 2024

Providing interpretable AI model metadata (for example, as factsheets ) specifying accountable persons, performance benchmarks (compared to human), data and methods used, audit records (date and by whom), and audit purpose and results. Capture key metadata to render AI models transparent and keep track of model inventory.

Metadata 91

Metadata Measurement Risk Modeling 91