Smart Data Collective

APRIL 13, 2021

In the modern world of business, data is one of the most important resources for any organization trying to thrive. Business data is highly valuable for cybercriminals. They even go after meta data. Big data can reveal trade secrets, financial information, as well as passwords or access keys to crucial enterprise resources.

Testing 124

Testing Behavioral Analytics Data-driven Big Data 124

Smart Data Collective

MARCH 27, 2020

The auto insurance industry has always relied on data analysis to inform their policies and determine individual rates. With the technology available today, there’s even more data to draw from. The good news is that this new data can help lower your insurance rate. Demographics. This includes: Age. Marital status.

Insurance 108

Insurance Measurement Risk Cost-Benefit 108

DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. In 2017, additional regulation targeted much smaller financial institutions in the U.S. The FDIC’s action was announced through a Financial Institution Letter, FIL-22-2017.

Risk 111

Risk Modeling IT Risk Management 111

Cloudera

SEPTEMBER 10, 2021

Across the federal government, agencies are struggling to identify, organize, analyze, and act on troves of data. It’s a problem that leaders are working actively to tackle, but they’re in a race against immeasurable volumes of data that is continuously being generated in perpetuity in stores known and unknown.

Machine Learning 66

Machine Learning Statistics Data-driven Big Data 66

Sisense

JANUARY 14, 2021

Especially when dealing with business data, trust in the figures is an essential element of every transaction. A reputation for stability and accuracy is critical in the fintech industry, dealing as it does with sensitive, high-impact data and security challenges. For analytics teams, trust is hard to gain and easy to lose.

Dashboards 85

Dashboards Testing Business Intelligence Interactive 85

datapine

NOVEMBER 19, 2019

No matter if you need to conduct quick online data analysis or gather enormous volumes of data, this technology will make a significant impact in the future. Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI.

Technology 279

Technology Internet of Things IT IoT 279

Domino Data Lab

MAY 8, 2019

For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105