Remove 2011 Remove Modeling Remove Reporting Remove Statistics
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What is Model Risk and Why Does it Matter?

DataRobot Blog

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. When business decisions are made based on bad models, the consequences can be severe. As machine learning advances globally, we can only expect the focus on model risk to continue to increase.

Risk 111
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A history of tech adaptation for today’s changing business needs

CIO Business Intelligence

Following this, in 2002, it began delivering its knowledge to customers in online format, using dashboards and interactive reports that provided easier and faster access to data and analysis. The initiative follows agile methodologies to offer faster and better results to its clients. js and React.js.

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Smarter Survey Results and Impact: Abandon the Asker-Puker Model!

Occam's Razor

If you are open to being challenged… then here are the short-stories inside this post… The World Needs Reporting Squirrels. Bonus #2: The Askers-Pukers Business Model. The World Needs Reporting Squirrels. If you are curious, here is a April 2011 post: The Difference Between Web Reporting And Web Analysis.

Modeling 127
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Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production.

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Big Data, Big Benefits: What Leaders Say

Sisense

These statistics highlight how large the task is to extract, transform, and load data that will be ready for analysis. As long ago as 2011, the McKinsey Global Institute estimated that retailers using data analytics at scale could increase their operating margins by more than 60 percent. analytics- and data-driven) or obsolete. ”.

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Fact-based Decision-making

Peter James Thomas

Integrity of statistical estimates based on Data. Having spent 18 years working in various parts of the Insurance industry, statistical estimates being part of the standard set of metrics is pretty familiar to me [7]. The thing with statistical estimates is that they are never a single figure but a range. million ± £0.5

Metrics 49
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Unlock The Power of Your Data With These 19 Big Data & Data Analytics Books

datapine

He founded the project Apache Storm in 2011, which turned to be “one of the world’s most popular stream processors and has been adopted by many of the world’s largest companies, including Yahoo!, Microsoft, Alibaba, Taobao, WebMD, Spotify, Yelp” according to Marz himself. The author also introduces the concept of “analytics 3.0”

Big Data 263