Smart Data Collective

MARCH 27, 2020

The good news is that this new data can help lower your insurance rate. Here is the type of data insurance companies use to measure a client’s potential risk and determine rates. Traditional data, like demographics, continues to be a factor in risk assessment. Demographics. This includes: Age. Occupation.

Insurance 107

Insurance Measurement Risk Cost-Benefit 107

Cloudera

FEBRUARY 23, 2023

Since the 1990s, opioid abuse in the US skyrocketed to the point that in 2017 the Department of Health and Human Services declared the opioid crisis a public health emergency. With the Controlled Substance Analytics platform online, KMC has eliminated manual data collection and streamlined data processing.

Data Analytics 75

Data Analytics Analytics Data Processing Risk 75

CIO Business Intelligence

MAY 16, 2023

higher [in 2022] than in 2017.” The inherent capabilities of AI–to process vast amounts of data and use learned intelligence to make decisions with extraordinary speed–enable opportunities uncovered through digital listening. Information governance enables enterprises to achieve strategic goals, mitigate risk, and reduce costs.

Advertising 104

Advertising Recreation/Entertainment Experimentation Enterprise 104

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. The Top 6 Benefits of Data Governance.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

The Unofficial Google Data Science Blog

APRIL 17, 2017

First, the system may not be understood, and even if it was understood it may be extremely difficult to measure the relationships that are assumed to govern its behavior. They can arise from data collection errors or other unlikely-to-repeat causes such as an outage somewhere on the Internet.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MAY 20, 2021

Working with highly imbalanced data can be problematic in several aspects: Distorted performance metrics — In a highly imbalanced dataset, say a binary dataset with a class ratio of 98:2, an algorithm that always predicts the majority class and completely ignores the minority class will still be 98% correct. Chawla et al. link] Fisher, R.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136