TDAN

JUNE 15, 2022

Given that the global big data market is forecast to be valued at $103 billion in 2027, it’s worth noticing. As the amount of data generated […]. “Information is the oil of the 21st century, and analytics is the combustion engine,” says Peter Sondergaard, former Global Head of Research at Gartner. And he has a point.

Data mining 98

Data mining Forecasting Big Data Marketing 98

Data Science 101

DECEMBER 11, 2019

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Every year they host an excellent and influential conference focusing on many areas of data science. Honestly, KDD has been promoting data science way before data science was even cool. 1989 to be exact. The details are below.

KDD 81

KDD Knowledge Discovery Data mining Data Science 81

FineReport

DECEMBER 19, 2019

For super rookies, the first task is to understand what data analysis is. Data analysis is a type of knowledge discovery that gains insights from data and drives business decisions. One is how to gain insights from the data. Data is cold and can’t speak. From Google. There are two points here.

Knowledge Discovery 98

Knowledge Discovery Visualization Reporting Data mining 98

The Unofficial Google Data Science Blog

JULY 22, 2020

A/B testing isn’t simple just because data is big — the law of large numbers doesn’t take care of everything! Even with big data, A/B tests require thinking deeply and critically about whether or not the assumptions made match the data. 2] Scott, Steven L. armed bandit experiments in the online service economy."

Experimentation 95

Experimentation Statistics Testing Knowledge Discovery 95

The Unofficial Google Data Science Blog

JANUARY 14, 2016

by AMIR NAJMI Running live experiments on large-scale online services (LSOS) is an important aspect of data science. But the fact that a service could have millions of users and billions of interactions gives rise to both big data and methods which are effective with big data.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

We could do this but in our big data world, we would avoid materializing such an inefficient structure by reducing the regression to its sufficient statistics. When solved with an intercept term, regression coefficients for the binary predictors are maximum likelihood estimates for the experiment effects under assumption of additivity.

Experimentation 40

Experimentation Statistics Metrics Measurement 40