DataRobot Blog

MAY 10, 2022

It has been over a decade since the Federal Reserve Board (FRB) and the Office of the Comptroller of the Currency (OCC) published its seminal guidance focused on Model Risk Management ( SR 11-7 & OCC Bulletin 2011-12 , respectively). To reference SR 11-7: .

Risk 64

Risk Modeling Machine Learning Data Quality 64

DataRobot Blog

MAY 26, 2022

When the FRB’s guidance was first introduced in 2011, modelers often employed traditional regression -based models for their business needs. While SR 11-7 is prescriptive in its guidance, one challenge that validators face today is adapting the guidelines to modern ML methods that have proliferated in the past few years.

Risk 52

Risk Modeling Metrics Business Objectives 52

Peter James Thomas

AUGUST 12, 2018

However, often the biggest stumbling block is a human one, getting people to buy in to the idea that the care and attention they pay to data capture will pay dividends later in the process. These and other areas are covered in greater detail in an older article, Using BI to drive improvements in data quality.

Metrics 49

Metrics Statistics Data Quality Measurement 49

datapine

APRIL 15, 2020

No matter if you need to develop a comprehensive online data analysis process or reduce costs of operations, agile BI development will certainly be high on your list of options to get the most out of your projects. The term “agile” was originally conceived in 2011 as a software development methodology.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

Ontotext

JULY 29, 2021

If you’ve used Google, you’ve used the cornucopia of Linked data across the Web, through Google’s Knowledge Graph (Google’s Knowledge Graph is reportedly supported by Freebase – the knowledge acquired by Google in 2010. )

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

datapine

AUGUST 29, 2022

Known as the person who coined the term Lambda Architecture, co-author Nathan Marz is a well-renowned expert in the field of big data and programming. Topics covered here range from backtesting and benchmarking approaches to data quality issues, software tools, and model documentation practices.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

The Unofficial Google Data Science Blog

JULY 18, 2023

We normally have lots of labelers and items in our dataset, and priors give a form of regularization that better handles cases where data might be sparse and makes the model less prone to overfitting. We derive our measurement of data quality, ICC, from the variance parameters in the model.$$

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52