FineReport

APRIL 9, 2024

One of the key aspects of the role of BI platforms is their ability to streamline the process of data analysis and decision-making. They offer functionalities that allow for the integration and transformation of raw data into meaningful and actionable insights.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

DataRobot

JULY 16, 2021

They all serve to answer the question, “How well can my model make predictions based on data?” In performance, the trust dimensions are the following: Data quality — the performance of any machine learning model is intimately tied to the data it was trained on and validated against.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

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. There are four groups of data that are naturally siloed: Structured data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

DataRobot Blog

MAY 26, 2022

To start with, SR 11-7 lays out the criticality of model validation in an effective model risk management practice: Model validation is the set of processes and activities intended to verify that models are performing as expected, in line with their design objectives and business uses.

Risk 52

Risk Modeling Metrics Business Objectives 52

Sisense

SEPTEMBER 3, 2020

Besides strong technical skills (for instance, use of Hadoop, programming in R and Python , math, statistics), data scientists should also be able to tackle open-ended questions and undirected research in ways that bring measurable business benefits to their organization. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

O'Reilly on Data

JULY 15, 2019

After the 2008 financial crisis, the Federal Reserve issued a new set of guidelines governing models— SR 11-7 : Guidance on Model Risk Management. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk. Model risk management. AI projects in financial services and health care.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

DataRobot Blog

JULY 21, 2022

Inquire whether there is sufficient data to support machine learning. Outline clear metrics to measure success. Document assumptions and risks to develop a risk management strategy. Discuss how the stakeholders want to interact with the machine learning model after it is built. Define project scope.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98