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. Conclusion.

Risk 52

Risk Modeling Metrics Business Objectives 52

erwin

MARCH 12, 2020

It also highlights select enterprise architecture management suite (EAMS) vendors based on size and functionality, including erwin. The report notes six primary EA competencies in which we excel in the large vendor category: modeling, strategy translation, risk management, financial management, insights and change management.

Enterprise 85

Enterprise Reporting Management ROI 85

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

Ontotext

FEBRUARY 26, 2024

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. Here’s how our tool makes it work. Let’s have a quick look under the bonnet.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

AWS Big Data

JANUARY 31, 2024

Transaction cost analysis (TCA) is widely used by traders, portfolio managers, and brokers for pre-trade and post-trade analysis, and helps them measure and optimize transaction costs and the effectiveness of their trading strategies. After your notebook is created, you will be redirected to the interactive notebook editor.

Marketing 85

Marketing Analytics Visualization Strategy 85

DataRobot Blog

JULY 21, 2022

If there is no forward-looking predictive component to the use case, it can probably be addressed with analytics and visualizations applied to historical data. Outline clear metrics to measure success. Document assumptions and risks to develop a risk management strategy. Not every project needs machine learning.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

Domino Data Lab

APRIL 3, 2019

Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for Edge caches become crucial for managing data on its way from web servers to mobile devices. Probably the best one-liner I’ve encountered is the analogy that: DG is to data assets as HR is to people. credit cards).

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. The ability to measure results (risk-reducing evidence). I double-dare you not to visualize that cohort! Or something.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

datapine

FEBRUARY 22, 2022

This includes defining the main stakeholders, assessing the situation, defining the goals, and finding the KPIs that will measure your efforts to achieve these goals. Improved risk management: Another great benefit from implementing a strategy for BI is risk management. Rely on interactive data visualizations.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

CIO Business Intelligence

APRIL 12, 2022

Even though Nvidia’s $40 billion bid to shake up enterprise computing by acquiring chip designer ARM has fallen apart, the merger and acquisition (M&A) boom of 2021 looks set to continue in 2022, perhaps matching the peaks of 2015, according to a report from risk management advisor Willis Towers Watson.

Enterprise 143

Enterprise Technology Consulting Software 143

Andrew White

JANUARY 11, 2021

Coding skills – SQL, Python or application familiarity – ETL & visualization? Value Management or monetization. Risk Management (most likely within context of governance). Product Management. measuring value, prioritizing (where to start), and data literacy? Governance. Architecture.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

NOVEMBER 16, 2022

Specific, measurable, achievable, relevant, and time-bound (SMART) actions should be presented. These might includes measurements related to: the intellectual resources of the company. management satisfaction. These might includes measurements related to: the intellectual resources of the company. management satisfaction.

Reporting 94

Reporting Software Key Performance Indicator Dashboards 94