The Unofficial Google Data Science Blog

JUNE 30, 2016

For example, in clinical trials, randomization may be unethical; in economics studies randomization is unfeasible in practice; and in marketing studies the potential cost of a lost business opportunity can make randomization unattractive. Identification We now discuss formally the statistical problem of causal inference.

Statistics 44

Statistics Optimization Modeling Experimentation 44

Jen Stirrup

OCTOBER 21, 2019

What happens if diversity is reduced to marketing, and the inclusion piece is forgotten? According to the Telegraph (2012), Female execs earn £423,390 less than men over careers. . What happens if a diversity issues bumps up against a marketing issue, for example? Office for National Statistics (2015) Gender Pay Gap.

Data-driven 48

Data-driven Marketing Testing Management 48

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

Data Science and Beyond

JULY 22, 2018

I got my first data science job in 2012, the year Harvard Business Review announced data scientist to be the sexiest job of the 21st century. Two years later, I published a post on my then-favourite definition of data science , as the intersection between software engineering and statistics. Things have changed considerably since 2012.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

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. MMM allows you to isolate incremental sales contributions coming from each of the marketing channels. What is MMM? Data Requirements.

Machine Learning 52

Machine Learning Sales Measurement ROI 52

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. This is an increase from 64.2 zettabytes of data in 2020, a tenfold increase from 6.5

Big Data 103

Big Data Data-driven Recreation/Entertainment Data Governance 103

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. Now, Google is spending what, 10 figures marketing TensorFlow? The good news is half the total of available market is not even started yet.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. They may contain parameters in the statistical sense, but often they simply contain strategically placed 0's and 1's indicating which bits of $alpha_t$ are relevant for a particular computation. by STEVEN L.

Forecasting 64

Forecasting Statistics Modeling Software 64

Domino Data Lab

AUGUST 8, 2019

following a breakthrough paper or two, plus changes in market microstructure). Another key point: troubleshooting edge cases for models in production—which is often where ethics and data meet, as far as regulators are concerned—requires much more sophistication in statistics than most data science teams tend to have. machine learning?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Alation

JULY 7, 2022

To answer these questions we need to look at how data roles within the job market have evolved, and how academic programs have changed to meet new workforce demands. In 2012 Davenport and Patil declared the data scientist was “ The Sexiest Job of the 21st Century.” Who would uncover secrets from these unknown landscapes?

Metadata 52

Metadata Data-driven Insurance Statistics 52

The Unofficial Google Data Science Blog

MAY 31, 2016

Such regions are often referred to as Generalized Market Areas (GMAs) or simply geos. The regions were originally formed based on television viewing behavior of their residents, clustering together “exclusive geographic area of counties in which the home market television stations hold a dominance of total hours viewed.”

Advertising 42

Advertising Testing Sales Statistics 42

datapine

DECEMBER 28, 2021

1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? If all this is true, what is the problem with statistics? What Is A Misleading Statistic?

Statistics 363

Statistics Advertising Visualization Data mining 363

Occam's Razor

SEPTEMBER 21, 2015

The Directors, the Marketers, the Optimization employees and our resident social media gurus. You understand a good amount of how this area of marketing works, you understand the company's goals. Second, between 2012 and 2013. conversion rate (it might not be statistically significant!). of your data-rich slide!).

Visualization 160

Visualization Key Performance Indicator Slice and Dice Strategy 160

Sisense

DECEMBER 11, 2019

These customer examples demonstrated how impactful smart data management and analytics can be for every part of customer organizations, from data teams to marketing, sales, and beyond. From a startup in 2012, it is now valued at $3.2 The company has integrated data analysis throughout its organization to power decision making.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

Occam's Razor

JANUARY 10, 2011

The smallest part of my success, and yours, will come from having the prefect implementation of the Omniture Marketing Suite or Google Analytics. 10% of your time should be spent in implementing tools, not 15 months with an eye towards analysis in the middle of 2012. You can win with Omniture or WebTrends or IBM or Google.

Analytics 120

Analytics Measurement Data-driven Optimization 120

Domino Data Lab

MARCH 3, 2019

After a data science conference, our marketing group wanted to follow-up by surveying 300 attendees from industry. That’s the point where models degrade once exposed to live customer data, and where it requires significant statistical expertise to answer even a simple “Why?” Surveying ABC adoption in enterprise.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

CIO Business Intelligence

FEBRUARY 3, 2023

Some vendors market their tools as “workflow automation” or “work process management.” Power Advisor tracks statistics about performance to locate bottlenecks and other issues. Pega wants to deliver “self-healing” and “self-learning” applications that can use AI and other statistics to recognize new opportunities for better automation.

Data-driven 145

Data-driven Interactive Enterprise Statistics 145

datapine

MAY 17, 2021

Studies say that more data has been generated in the last two years than in the entire history before and that since 2012 the industry has created around 13 million jobs around the world. With the growth of data in the past years, so has grown the offer of tools available in the market. 2) Be quick.

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161