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

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

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

OCTOBER 24, 2019

While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. And to truly understand it , you need to be able to create and sustain an enterprise-wide view of and easy access to underlying metadata. This isn’t an easy task.

Metadata 104

Metadata Management Data-driven Data Architecture 104

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

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 76

Risk Management Risk Metrics Machine Learning 76

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

IBM Big Data Hub

FEBRUARY 22, 2024

Earning trust in the outputs of AI models is a sociotechnical challenge that requires a sociotechnical solution. There must be a concerted effort to make these principles a reality through consideration of the functional and non-functional requirements in the models and the governance systems around those models.

Metadata 96

Metadata Measurement Risk Modeling 96

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

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

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.

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

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

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