Remove 2009 Remove Measurement Remove Metrics Remove Testing
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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

Metrics 156
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Understanding Simpson’s Paradox to Avoid Faulty Conclusions

Sisense

One of the simplest ways to start exploring your data is to aggregate the metrics you are interested in by their relevant dimensions. A new drug promising to reduce the risk of heart attack was tested with two groups. They measured both the blood pressure of the participants and if they had a heart attack or not.

Testing 104
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The Importance Of Financial Reporting And Analysis: Your Essential Guide

datapine

Utilizing financial data with the help of online data analysis tools allows you to not only share vital information both internally and externally but also leverage metrics or insights to make significant improvements to the very area that allows your business to flow. firm Kraft, in 2009, it reported IFRS-based profits of $690 million.

Reporting 248
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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

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. return synthetic. Chawla et al.,

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Is Your Brand Magnificent At Digital Marketing? A Diagnostic Framework.

Occam's Razor

It is not just what you do to attract traffic (what most people think of as marketing and advertising), but also what types of experiences you create (something people rarely think is marketing) and how good you are at delivering for where you should be in 2013 rather than 2009 (only the rarest of marketers think with this lens on).

Marketing 147
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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

Visualizations are vital in data science work, with the caveat that the information that they convey may be 4-5 layers of abstraction away from the actual business process being measured. measure the subjects’ ability to trust the models’ results. Information can get quite distorted after being abstracted that many times.

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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

For example, in regards to marketing, traditional advertising methods of spending large amounts of money on TV, radio, and print ads without measuring ROI aren’t working like they used to. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. The results?