The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

DataKitchen

SEPTEMBER 21, 2023

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Crucially, it takes into account the uncertainty inherent in our experiments. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

CIO Business Intelligence

APRIL 28, 2024

However, new energy is restricted by weather and climate, which means extreme weather conditions and unpredictable external environments bring an element of uncertainty to new energy sources. We also need to create space for market-oriented interaction. This includes participating in peak regulation according to user market behavior.

Interactive 95

Interactive Uncertainty Data Collection IoT 95

datapine

SEPTEMBER 4, 2023

Table of Contents 1) The Benefits Of Data Visualization 2) Our Top 27 Best Data Visualizations 3) Interactive Data Visualization: What’s In It For Me? Whether static or interactive dashboards , these creative data visualization examples will serve as an inspiration for any data enthusiast. No, data is the new soil.”

Interactive 264

Interactive Visualization Cost-Benefit Dashboards 264

O'Reilly on Data

SEPTEMBER 15, 2020

This in turn would increase the platform’s value for users and thus increase engagement, which would result in more eyes to see and interact with ads, which would mean better ROI on ad spend for customers, which would then achieve the goal of increased revenue and customer retention (for business stakeholders).

Cost-Benefit 293

Cost-Benefit Advertising ROI Machine Learning 293

Occam's Razor

JULY 12, 2010

Let's go look at some tools… Measuring "Invisible Virality": Tynt. It measures how often a blog post is tweeted/retweeted. I also measure the # of Comments Per Post as a measure of how "engaging" / "valuable" people found the content to be. Or for that matter how many tools.

Analytics 96

Analytics Measurement Metrics KPI 96

Cloudera

OCTOBER 26, 2021

The challenges of remote working with dispersed teams have been a test of leadership. In these circumstances, empathy needs to underscore every interaction. . Maintaining regular interactions with your teams sends a signal that you value their work. Lean in and not away. Emphasise commitment in times of change.

Uncertainty 87

Uncertainty Interactive Reporting Measurement 87

Domino Data Lab

JUNE 23, 2019

As a result, Skomoroch advocates getting “designers and data scientists, machine learning folks together and using real data and prototyping and testing” as quickly as possible. These measurement-obsessed companies have an advantage when it comes to AI. It is similar to R&D. Transcript. Hi, I’m Peter Skomoroch.

Management 110

Management Machine Learning Experimentation Metrics 110

The Unofficial Google Data Science Blog

APRIL 19, 2021

To explain, let’s borrow a quote from Nate Silver’s The Signal and the Noise : One of the most important tests of a forecast — I would argue that it is the single most important one — is called calibration. For these ML systems, calibration simplifies interaction. bar{pi} (1 - bar{pi})$: This is the irreducible loss due to uncertainty.

Modeling 122

Modeling IT Metrics Testing 122

The Unofficial Google Data Science Blog

APRIL 16, 2019

Such decisions involve an actual hypothesis test on specific metrics (e.g. The metrics to measure the impact of the change might not yet be established. Typically, it takes a period of back-and-forth between logging and analysis to gain the confidence that a metric is actually measuring what we designed for it to measure.

Experimentation 68

Experimentation Sales Metrics Measurement 68

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

The beliefs of this community are always evolving, and the process of thoughtfully generating, testing, refuting and accepting ideas looks a lot like Science. These quasi-explanations usually involve large, real effects and interactions so complex that arguments based on them are often non-falsifiable.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

Jet Global

APRIL 8, 2021

How prepared are they, though, for the different sets of risks and opportunities associated with long-term uncertainties? For example, how well are they accounting for the long-term impacts of multiple government measures being introduced globally in response to recent crises, such as the COVID-19 pandemic? Preparing for uncertainty.

Forecasting 52

Forecasting Reporting Uncertainty Key Performance Indicator 52

O'Reilly on Data

JUNE 16, 2020

But when making a decision under uncertainty about the future, two things dictate the outcome: (1) the quality of the decision and (2) chance. This essay is about how to take a more principled approach to making decisions under uncertainty and aims to provide certain conceptual and cognitive tools for how to do so, not what decisions to make.

Uncertainty 275

Uncertainty Testing Risk Reporting 275