IBM Big Data Hub

OCTOBER 4, 2022

Manual processes that introduce risk and make it hard to scale. Multiple unsupported tools for building and deploying models. According to Gartner 54% of models are stuck in pre-production because there is not an automated process to manage these pipelines and there is a need to ensure the AI models can be trusted.”

Metadata 99

Metadata Risk Risk Management Experimentation 99

Octopai

JUNE 19, 2023

Catalogs also allow for better Risk Management; data catalogs help businesses maintain regulatory compliance by providing a clear record of what data is stored and how it’s used. Automate Metadata Capture Leverage metadata management tools like Octopai to automate the process of capturing metadata from various sources.

Metadata 88

Metadata Data Governance Measurement Risk Management 88

IBM Big Data Hub

MAY 9, 2023

According to Gartner , 54% of models are stuck in pre-production because there is not an automated process to manage these pipelines and there is a need to ensure the AI models can be trusted. This solution is designed to include everything needed to develop a consistent transparent model management process.

Metadata 75

Metadata Risk Experimentation Dashboards 75

erwin

JULY 12, 2019

Creating and automating a curated enterprise data catalog , complete with physical assets, data models, data movement, data quality and on-demand lineage. Activating their metadata to drive agile data preparation and governance through integrated data glossaries and dictionaries that associate policies to enable stakeholder data literacy.

Data Governance 110

Data Governance Management Metadata Risk Management 110

IBM Big Data Hub

APRIL 20, 2023

Banks and their employees place trust in their risk models to help ensure the bank maintains liquidity even in the worst of times. This trust depends on an understanding of the data that inform risk models: where does it come from, where is it being used, and what are the ripple effects of a change?

Risk 71

Risk Risk Management Reporting Metadata 71

IBM Big Data Hub

DECEMBER 4, 2023

The Board recently published its point of view on foundation models addressing the risks that generative AI poses. Its toolkit automates risk management, monitors models for bias and drift, captures model metadata and facilitates collaborative, organization-wide compliance.

Consulting 78

Consulting Risk Metadata Risk Management 78

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

JULY 8, 2022

The eight questions are drawn from topics such as ADM phases, adapting the ADM, architecture content framework, TOGAF reference models, and the architecture capability framework. . Integrating Risk and Security Certification. Enterprise Architecture, Enterprise Architecture Modeling, and Digital Enterprise Architecture.

Risk Management 96

Risk Management Risk Enterprise Metadata 96

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

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

Achieving Responsible AI As building and scaling AI models for your organization becomes more business critical, achieving Responsible AI (RAI) should be considered a highly relevant topic. This necessitates the detection of bias during data acquisition, building, training, deploying and monitoring models. billion by 2025.

Risk Management 52

Risk Management Risk Modeling Metadata 52

Ontotext

FEBRUARY 26, 2024

The answers to these foundational questions help you uncover opportunities and detect risks. Further, RED’s underlying model can be visually extended and customized to complex extraction and classification tasks. Risk management : Understanding the correlation between events and stock price fluctuations helps manage risk.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

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

SEPTEMBER 20, 2022

But these organizations need to be able to trust their AI/ML models before they can be operationalized and used in crucial business processes. These days, if an AI model makes a biased, unfair decision involving the health, wealth or well-being of humans, an organization can hit the news for the wrong reasons. Is it scalable?

Metadata 56

Metadata Machine Learning Data-driven Modeling 56

CIO Business Intelligence

SEPTEMBER 23, 2022

To better understand why a business may choose one cloud model over another, let’s look at the common types of cloud architectures: Public – on-demand computing services and infrastructure managed by a third-party provider and shared with multiple organizations using the public Internet. Hybrid – a mix of public and private clouds.

Data Processing 88

Data Processing Metadata Cost-Benefit Risk Management 88

erwin

SEPTEMBER 3, 2020

You can collect complete application ecosystem information; objectively identify connections/interfaces between applications, using data; provide accurate compliance assessments; and quickly identify security risks and other issues. Automating Data Governance and Enterprise Architecture. Automating Data Governance and Enterprise Architecture.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

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. IRB (internal-ratings based) models were absolutely fine under Basel II.

Management 52

Management Risk Management Risk Visualization 52

erwin

NOVEMBER 13, 2020

Data Security & Risk Management. Innovation Management. Enterprise architecture has been critical to helping businesses navigate the pandemic to ensure business continuity, reimagine their business and operating models, and identify the tools to survive and ultimately thrive in a post-COVID world. Cloud Migration.

Enterprise 131

Enterprise Digital Transformation Key Performance Indicator Data-driven 131

CIO Business Intelligence

APRIL 28, 2023

To better understand why a business may choose one cloud model over another, let’s look at the common types of cloud architectures: Public – on-demand computing services and infrastructure managed by a third-party provider and shared with multiple organisations using the public internet. Hybrid – a mix of public and private clouds.

Data Processing 54

Data Processing Metadata Cost-Benefit Risk Management 54

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. Reporting. Traceability and Accountability. Conclusion.

Metadata 59

Metadata Finance Cost-Benefit Data Quality 59

erwin

APRIL 4, 2019

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. For example: Data ownership model showing a data item, its definition, producers, consumers, stewards and quality rules (for profiling).

Data Governance 75

Data Governance Data Quality Risk Management Data-driven 75

AWS Big Data

MARCH 27, 2023

Developers, data scientists, and analysts can work across databases, data warehouses, and data lakes to build reporting and dashboarding applications, perform real-time analytics, share and collaborate on data, and even build and train machine learning (ML) models with Redshift Serverless.

Data Warehouse 87

Data Warehouse Management Snapshot Data Lake 87

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

Ontotext

MAY 5, 2023

It is reused in modeling the publication of entity data or regulatory-mandated data exchange, as seen in the example provided below. An IT manager might be dealing with software, hardware and data, while an expert might make further distinctions in each category (for example between laptops, servers, mobile devices, etc.).

Data Collection 64

Data Collection Risk Data-driven Interactive 64

erwin

OCTOBER 3, 2019

As a matter of fact, Gartner has said that EA is becoming a “form of internal management consulting” because it helps define and shape business and operating models, identify risk and opportunities, and create technology roadmaps to suit. to help provide stakeholders with a thorough understanding of the enterprise.

Enterprise 111

Enterprise Cost-Benefit Data-driven Risk 111

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. Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. There are models everywhere.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

AUGUST 14, 2023

Taken together, the posts in this series lay out some possible operating models for data mesh within an organization. Approves changes to DPPM principles and operating model. Approves changes to the domain data model and domain data product portfolio. Kudzu Kudzu—or kuzu (クズ)—is native to Japan and southeast China.

Management 81

Management Risk Measurement Optimization 81

Alation

FEBRUARY 8, 2022

Data mesh inverts the common model of having a centralized team (such as a data engineering team), who manage and transform data for wider consumption. Data mesh supporters argue that this centralized model is no longer tenable in the expanding data universe of the enterprise. That model has failed to support rapid data growth.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

Cloudera

JANUARY 22, 2019

Cloudera Enterprise is a one-stop shop for running analytics models and algorithms against multiple data sources across on-premises and cloud, and sometimes real-time data sources. Shared Data Catalog to preserve context and enforce Governance.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Laminar Security

NOVEMBER 16, 2023

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. A transparent and fair pricing model that suits your budget and needs. DSPM enriches the data security intelligence of SIEM.

Risk 59

Risk Cost-Benefit Dashboards Management 59

Grooper

OCTOBER 23, 2019

With the increasing value of data and more tools to process and analyze information than ever before, companies with information governance and master data model programs are outpacing their peers. Now is the time to get organized, and view information management as the single most important initiative for business growth and innovation.

Metrics 59

Metrics Measurement Strategy Optimization 59

Andrew White

JANUARY 11, 2021

How do you think Technology Business Management plays into this strategy? Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. Value Management or monetization. Product Management. Governance. Architecture.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52