Smart Data Collective

FEBRUARY 1, 2023

Big data is especially important for the nursing sector. A 2017 study from Harvard Medical School discusses some of the changes big data has created for nurses. There are more ways than ever to provide high-quality healthcare evaluations, and data collection remotely. It’s a big deal. So, what’s out there?

Data Analytics 143

Data Analytics Analytics Big Data Internet of Things 143

Domino Data Lab

MAY 20, 2021

Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. Insufficient training data in the minority class — In domains where data collection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

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. McKinsey & Company’s 2022 Global Survey on AI says , “AI adoption globally is 2.5x

Advertising 105

Advertising Recreation/Entertainment Experimentation Data Collection 105

Alation

AUGUST 26, 2021

Data intelligence first emerged to support search & discovery, largely in service of analyst productivity. For years, analysts in enterprises had struggled to find the data they needed to build reports. This problem was only exacerbated by explosive growth in data collection and volume. HBR Review May/June 2017.

Metadata 64

Metadata Data Governance Dashboards Software 64

Domino Data Lab

OCTOBER 23, 2019

The first step to collecting all of the data is to figure out which data source to collect first, and where to get it. Knowing that the ultimate goal is to compare the social-media influence and power of NBA players, a great place to start is with the roster of the NBA players in the 2016–2017 season. 35,vjust=1).

Statistics 59

Statistics Machine Learning Testing Modeling 59

Occam's Razor

SEPTEMBER 15, 2014

They will need two different implementations, it is quite likely that you will end up with two sets of metrics (more people focused for mobile apps, more visit focused for sites). In this post we will look mobile sites first, both data collection and analysis, and then mobile applications. And again, a custom set of metrics.

Metrics 143

Metrics Reporting Analytics Marketing 143

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