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5 hot IT hiring trends — and 5 going cold

CIO Business Intelligence

Because of economic uncertainty, about 40% of CIOs slowed hiring as 2022 wound down, and about 30% experienced hiring freezes. Cold: Poaching high performers Market uncertainties have made recruiting more difficult in surprising ways, says Dru Kirk, vice president of talent acquisition for Marqeta.

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Perform time series forecasting using Amazon Redshift ML and Amazon Forecast

AWS Big Data

Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future. Many businesses use different software tools to analyze historical data and past patterns to forecast future demand and trends to make more accurate financial, marketing, and operational decisions.

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What IT executives are saying about vendor consolidation

CIO Business Intelligence

While there is little doubt that companies have been cutting back on expenses generally in response to economic uncertainty, startups in particular have been feeling the pain of contracting budgets and reluctant investors. At this point in time, it needs to be asked whether such a rapid increase in the number of vendors is sustainable.

IT 117
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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Crucially, it takes into account the uncertainty inherent in our experiments. There is also uncertainty related to our modeling choices — did we select the correct polynomial embedding function $f(x)$, or is the true relationship better described by a different polynomial embedding?

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Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

Quantification of forecast uncertainty via simulation-based prediction intervals. In the first plot, the raw weekly actuals (in red) are adjusted for a level change in September 2011 and an anomalous spike near October 2012. Prediction Intervals A statistical forecasting system should not lack uncertainty quantification.

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Data Science, Past & Future

Domino Data Lab

I went to a meeting at Starbucks with the founder of Alation right before they launched in 2012, drawing on the proverbial back-of-the-napkin. They learned about a lot of process that requires that you get rid of uncertainty. They’re being told they have to embrace uncertainty. You started to see point solutions.

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Estimating the prevalence of rare events — theory and practice

The Unofficial Google Data Science Blog

The bucketing method also changes the importance sampling to a stratified sampling setting, and allows us to use binomial confidence intervals to estimate the uncertainty of our estimate (more on that later). 5] Ray Chambers, Robert Clark (2012). Whether or not we borrow strength from other scores also impacts the estimation.

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