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

JULY 29, 2021

One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases. There are more than 80 million pages with semantic, machine interpretable metadata , according to the Schema.org standard. Take this restaurant, for example.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production.

Machine Learning 244

Machine Learning Technology Deep Learning Data Science 244

Cloudera

JUNE 7, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. And, as Deloitte put it: “Hybrid cloud is the de facto model”. . Integration, metadata and governance capabilities glue the individual components together.” .

IT 112

IT Data Architecture Unstructured Data Big Data 112

CIO Business Intelligence

JUNE 23, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. And, as Deloitte put it: “Hybrid cloud is the de facto model”. . Integration, metadata and governance capabilities glue the individual components together.” .

IT 73

IT Data Architecture Unstructured Data Big Data 73

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

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Another way to find the metric you want to change is to look at your business model. The business model also tells you what the metric should be.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156