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7 famous analytics and AI disasters

CIO Business Intelligence

MIT Technology Review has chronicled a number of failures, most of which stem from errors in the way the tools were trained or tested. Lee noted that Tay’s predecessor, Xiaoice, released by Microsoft in China in 2014, had successfully had conversations with more than 40 million people in the two years prior to Tay’s release.

Analytics 145
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What Are the Most Important Steps to Protect Your Organization’s Data?

Smart Data Collective

By 2012, there was a marginal increase, then the numbers rose steeply in 2014. One of the best solutions for data protection is advanced automated penetration testing. Based on figures from Statista , the volume of data breaches increased from 2005 to 2008, then dropped in 2009 and rose again in 2010 until it dropped again in 2011.

Testing 131
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Billie Inspires Customer Trust with Tool to Improve Dashboard Reliability

Sisense

With that in mind, the developers at Billie came up with the idea to automatically test Sisense charts. This meant that we could access and test all of the charts by simply cloning the corresponding Git repository and running the code for each chart.”. Run the queries and store the results for later analysis of tests.

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Regeneron turns to IT to accelerate drug discovery

CIO Business Intelligence

billion company’s scientific, commercial, and manufacturing businesses since joining the company in 2014. For McCowan, the key is to give scientists any and all tools that allow them to explore their hypotheses and test theories. It is all about the data. “And From a language perspective, scientists use Python and Jupyter Notebooks.

Data Lake 124
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The Data Visualization Design Process: A Step-by-Step Guide for Beginners

Depict Data Studio

Apply the Squint Test In these before scatter plot on the left, the cluttered appearance distracts us from the data. Apply the Squint Test. I like to test my drafts ahead of time to make sure they’ll still be legible even if they’re printed in grayscale. You can test your drafts a couple of different ways.

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The curse of Dimensionality

Domino Data Lab

MANOVA, for example, can test if the heights and weights in boys and girls is different. This statistical test is correct because the data are (presumably) bivariate normal. In high dimensions the data assumptions needed for statistical testing are not met. Statistical methods for analyzing this two-dimensional data exist.

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What is DataOps? Principles and Benefits

Octopai

Common elements of DataOps strategies include: Collaboration between data managers, developers and consumers A development environment conducive to experimentation Rapid deployment and iteration Automated testing Very low error rates. But the approaches and principles that form the basis of DataOps have been around for decades.