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

Smart Data Collective

OCTOBER 17, 2022

zettabytes in 2012. Consider the statistics from Domo that the number of home-based workers has increased from roughly 15% 18 months ago to more than 50% now (it was close to 100% at times during the epidemic). That’s a lot of data per person on our little globe, by any measure. This is an increase from 64.2

Big Data 110

Big Data Data-driven Recreation/Entertainment Data Governance 110

Data Science and Beyond

JANUARY 11, 2020

I learned about Bayesian statistics and conjugate priors. Towards the end of my PhD in 2012, I got into Kaggle competitions. In reality, problem definition and solution measurement are more challenging and important. Sentiment analysis is a commodity – using it in practice is a software engineering problem.

Software 103

Software Data Science Machine Learning Deep Learning 103

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

AWS Big Data

APRIL 3, 2024

By analyzing the historical report snapshot, you can identify areas for improvement, implement changes, and measure the effectiveness of those changes.

Data Quality 96

Data Quality Visualization Metadata Metrics 96

The Unofficial Google Data Science Blog

JUNE 30, 2016

A naïve comparison of the exposed and unexposed groups would produce an overly optimistic measurement of the effect of the ad, since the exposed group has a higher baseline likelihood of purchasing a pickup truck. Identification We now discuss formally the statistical problem of causal inference. we drop the $i$ index.

Statistics 44

Statistics Optimization Modeling Experimentation 44

The Unofficial Google Data Science Blog

MAY 31, 2016

It is important that we can measure the effect of these offline conversions as well. Panel studies make it possible to measure user behavior along with the exposure to ads and other online elements. Let's take a look at larger groups of individuals whose aggregate behavior we can measure. days or weeks).

Advertising 42

Advertising Testing Sales Statistics 42

Occam's Razor

JANUARY 10, 2011

10% of your time should be spent in implementing tools, not 15 months with an eye towards analysis in the middle of 2012. And possess at least some knowledge of the fundamentals of statistics. Use Kissmetrics or 4Q and measure primary purpose by task completion. I can't measure if the person voted.

Analytics 121

Analytics Measurement Data-driven Optimization 121

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. Statistical Science. Statistics in Biopharmaceutical Research, 2010. [4] 5] Ray Chambers, Robert Clark (2012). 7] Neyman, J.

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 128

Big Data Data-driven Unstructured Data Marketing 128

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

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

Domino Data Lab

SEPTEMBER 25, 2019

We see it when working with log data, financial data, transactional data, and when measuring anything in a real engineering system. A big part of statistics, particularly for financial and econometric data, is analyzing time series, data that are autocorrelated over time. Time series data is commonly encountered. > attGarch.

Forecasting 87

Forecasting Modeling Statistics Optimization 87

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

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. They support statistical analysis through guided advanced analytics attributes that are ready immediately upon implementation.

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161

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

Edwin Chen

JANUARY 7, 2013

debates — Romney’s Binder (@RomneysBinder) October 17, 2012. Behind the scenes: we run a Storm topology that tracks statistics on search queries. — Sohaib Athar (@ReallyVirtual) May 1, 2011. Or when Mitt Romney mentioned binders during the presidential debates. Boy, I’m full of women!

Statistics 73

Statistics Machine Learning Advertising Metadata 73