Domino Data Lab

AUGUST 8, 2019

Their approach is to bombard “organoid” mini brains living in vats with potential cancer meds, to measure the meds’ relative effects. Putting discussions about security aside, the statistics competency required to confront fairness and bias issues for machine learning models in production set quite a high bar. machine learning?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

The Unofficial Google Data Science Blog

AUGUST 27, 2019

But importance sampling in statistics is a variance reduction technique to improve the inference of the rate of rare events, and it seems natural to apply it to our prevalence estimation problem. There are many strategies we can use to estimate this quantity, and we will discuss each option in detail. Statistical Science.

Metrics 98

Metrics Statistics Uncertainty Optimization 98

Occam's Razor

MARCH 12, 2012

Clickstream + qualitative data + rigorous statistical analysis of outcomes + deep mining of data from competitive intelligence sources + rapid experiments + more. Avoiding big disappointment and the hows were on my mind as I prepared my keynote for Strata 2012 Big Data conference.

Big Data 127

Big Data Data-driven Unstructured Data Marketing 127

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. More people than ever are using statistical analysis packages and dashboards, explicitly or more often implicitly, to develop and test hypotheses. This question is statistical or methodological in nature. Know what matters.

Experimentation 61

Experimentation Testing Statistics Metrics 61

The Unofficial Google Data Science Blog

APRIL 17, 2017

First, the system may not be understood, and even if it was understood it may be extremely difficult to measure the relationships that are assumed to govern its behavior. 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.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Smart Data Collective

OCTOBER 17, 2022

This proliferation of data and the methods we use to safeguard it is accompanied by market changes — economic, technical, and alterations in customer behavior and marketing strategies , to mention a few. zettabytes in 2012. That’s a lot of data per person on our little globe, by any measure. This is an increase from 64.2

Big Data 105

Big Data Data-driven Recreation/Entertainment Data Governance 105

DataRobot Blog

APRIL 4, 2022

MMM stands for Marketing Mix Model and it is one of the oldest and most well-established techniques to measure the sales impact of marketing activity statistically. As with any type of statistical model, data is key and GIGO (“Garbage In, Garbage Out”) principle definitely applies. What cannot be measured? What is MMM?

Machine Learning 52

Machine Learning Sales Measurement ROI 52

Sisense

DECEMBER 11, 2019

The challenge is to do it right, and a crucial way to achieve it is with decisions based on data and analysis that drive measurable business results. He outlined how critical measurable results are to help VCs make major investment decisions — metrics such as revenue, net vs gross earnings, sales , costs and projections, and more.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

datapine

MAY 17, 2021

Businesses can benefit from improved data driven decision making as well as enhanced business processes and models and share insights across departments more fluently while propelling intelligent business strategies. For example, the marketing team should be able to quickly access IT metrics to support their e-commerce strategies.

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161