Remove 2011 Remove Experimentation Remove Testing
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6 enterprise DevOps mistakes to avoid

CIO Business Intelligence

Driven by the development community’s desire for more capabilities and controls when deploying applications, DevOps gained momentum in 2011 in the enterprise with a positive outlook from Gartner and in 2015 when the Scaled Agile Framework (SAFe) incorporated DevOps. It may surprise you, but DevOps has been around for nearly two decades.

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The mainframe is dying: Long live the mainframe application!

CIO Business Intelligence

years, a record it shares with the z114, launched in September 2011 and destined to be supported through December 2022. Wazi is a suite of tools IBM introduced back in 2020 with which developers can write z/OS applications and then test them in a z/OS sandbox on their own x86 hardware. years after its launch in June 2006.

Sales 130
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Why CEOs should test big digital business ideas in tiny countries.

Mark Raskino

The President of Iceland Olafur Ragnar Grimsson explained this phenomenon to me when I had the privilege to interview him in 2011 (Gartner Report: G00212784 ). “So He was talking about something we call the ‘compound uncertainty’ that must be navigated when we want to test and introduce a real breakthrough digital business idea.

Testing 53
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Further Exploration #13: 3D Treemap Spheres and Cylinders

The Data Visualisation Catalogue

This visualisation was created in 2011 by Hans-Jörg Schulz, Steffen Hadlak and Heidrun Schumann in their paper The Design Space of Implicit Hierarchy Visualization: A Survey (p. This experimental visualisation uses a polar layout and extends into into 3D with a cylindrical form. 3D Polar Treemap. 3D Polar Steptree.

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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

A/B testing is used widely in information technology companies to guide product development and improvements. For questions as disparate as website design and UI, prediction algorithms, or user flows within apps, live traffic tests help developers understand what works well for users and the business, and what doesn’t.

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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

It was first defined by the US Federal Reserve and Office of the Comptroller of the Currency ( SR 11-7 ) in April 2011. The process of doing data science is about learning from experimentation failures, but inadvertent errors can create enormous risks in model implementation. Model implementation. Model Risk Management Framework.

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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature. Identify, hypothesize, test, react. But at the same time, they had to have a real test of an actual feature. You don’t need a beautiful beast to go out and test.

Metrics 157