Occam's Razor

SEPTEMBER 29, 2009

One of the ultimate excuses for not measuring impact of Marketing campaigns is: "Oh, that's just a branding campaign." If supported by "data" then it tends to be of the most fragile kind (usually the the fact that the CEO saw it during the Super Bowl and felt happy suffices as actionable data).

Measurement 128

Measurement Metrics Analytics Marketing 128

Sisense

JANUARY 21, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. One of the simplest ways to start exploring your data is to aggregate the metrics you are interested in by their relevant dimensions. How can good data lead to faulty conclusions? How does this happen? 9/10 = 90%.

Testing 104

Testing Risk Data-driven Statistics 104

John Wheeler

NOVEMBER 25, 2020

Integrated risk management (IRM) technology is uniquely suited to address the myriad of risks arising from the current crisis and future COVID-19 recovery. Re-starting business operations will require risk visibility not only across the organization but vertically down through the organization as well. Key Findings.

Marketing 110

Marketing Risk Management Risk Digital Transformation 110

Domino Data Lab

MAY 20, 2021

Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. This renders measures like classification accuracy meaningless. 1988), E-state data (Hall et al., Their tests are performed using C4.5-generated Pima Indian Diabetes (Smith et al., 1998) and others).

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Peter James Thomas

AUGUST 12, 2018

These normally appear at the end of an article, but it seemed to make sense to start with them in this case: Recently I published Building Momentum – How to begin becoming a Data-driven Organisation. A number of factors can play into the accuracy of data capture. Honesty of Data that is captured. Timing issues with Data.

Metrics 49

Metrics Statistics Data Quality Measurement 49

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. ML model interpretability and data visualization. back to the structure of the dataset.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

datapine

DECEMBER 28, 2021

Statistics are infamous for their ability and potential to exist as misleading and bad data. Exclusive Bonus Content: Download Our Free Data Integrity Checklist. Get our free checklist on ensuring data collection and analysis integrity! To get this journey started let’s look at the misleading statistics definition.

Statistics 363

Statistics Advertising Visualization Data mining 363