The Unofficial Google Data Science Blog

JUNE 30, 2016

Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation. The field of statistical machine learning provides a solution to this problem, allowing exploration of larger spaces. For a random sample of units, indexed by $i = 1.

Statistics 44

Statistics Optimization Modeling Experimentation 44

Jen Stirrup

OCTOBER 21, 2019

I am mentoring and leading them, while delivering the project, setting a vision, generating and implementing data strategies, and slowly helping to mould the culture to be more data-driven as well as insight-driven. According to the Telegraph (2012), Female execs earn £423,390 less than men over careers. . & Kamenou-Aigbekaen, N.

Data-driven 48

Data-driven Marketing Testing Management 48

Occam's Razor

MAY 14, 2012

It used to fall behind lag the other two in brand queries, but you can see how starting late 2009 (bad year for Target in this context) Amazon overtook Target and now (2011, 2012) is casting a big shadow over Target. Brand strength is built over time using online and offline advertising.

Measurement 128

Measurement Analytics Advertising Marketing 128

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

AWS Big Data

JUNE 28, 2023

Challenges Customers across industries today are looking to increase revenue and customer engagement by implementing near-real time analytics use cases like personalization strategies, fraud detection, inventory monitoring, and many more. Choose Create policy.

Data Warehouse 81

Data Warehouse Analytics Metrics Dashboards 81

The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. It is also a sound strategy when experimenting with several parameters at the same time. And sometimes even if it is not[1].)

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

The Unofficial Google Data Science Blog

APRIL 17, 2017

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. Prediction Intervals A statistical forecasting system should not lack uncertainty quantification. Journal of Official Statistics 6.1 Specifically, see "1.4 2] Cleveland, Robert B.,

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. 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

APRIL 21, 2021

In contrast, the decision tree classifies observations based on attribute splits learned from the statistical properties of the training data. Machine Learning-based detection – using statistical learning is another approach that is gaining popularity, mostly because it is less laborious. 3f" % x) dataDF.describe().

Statistics 69

Statistics Machine Learning Modeling Metrics 69

AWS Big Data

MARCH 21, 2024

Challenges Customers across industries today are looking to use data to their competitive advantage and increase revenue and customer engagement by implementing near real time analytics use cases like personalization strategies, fraud detection, inventory monitoring, and many more. Choose Create policy.

Data Warehouse 83

Data Warehouse Metrics Statistics Optimization 83

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 is MMM? Data Requirements.

Machine Learning 52

Machine Learning Sales Measurement ROI 52

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

Domino Data Lab

AUGUST 8, 2019

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. It’s a quick way to clear the room. machine learning? Or something. Nothing Spreads Like Fear”.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Occam's Razor

SEPTEMBER 21, 2015

We are going to discuss a cluster of strategies you can use to ensure that you present your message with radical simplicity and with an incredible focus. Don't underestimate the value of this strategy in your storytelling. Second, between 2012 and 2013. Here's the resulting output. Simpler, right? Just, less stuff.

Visualization 160

Visualization Key Performance Indicator Slice and Dice Strategy 160

Sisense

DECEMBER 11, 2019

These teams now play a far more significant part in shaping company strategy than ever before, because the opportunity of Big Data necessitated skilled data professionals not just to crunch the numbers but to find value in the information. From a startup in 2012, it is now valued at $3.2 The impact on customers. A true unicorn.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

The Unofficial Google Data Science Blog

MARCH 31, 2016

We often use statistical models to summarize the variation in our data, and random effects models are well suited for this — they are a form of ANOVA after all. Cambridge University Press, (2012). [4] Journal of the American Statistical Association 68.341 (1973): 117-130. [5] Journal of the American Statistical Association, Vol.

Modeling 40

Modeling Statistics Advertising Testing 40

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. 5: Embrace agility, nimbleness & a portfolio strategy. You can win with Omniture or WebTrends or IBM or Google. Total data-gasm.

Analytics 120

Analytics Measurement Data-driven Optimization 120

Domino Data Lab

MARCH 3, 2019

While image data has been the stalwart for deep learning use cases since the proverbial “ AlexNet moment ” in 2011-2012, and a renaissance in NLP over the past 2-3 years has accelerated emphasis on text use cases, we note that structured data is at the top of the list in enterprise. Spark, Kafka, TensorFlow, Snowflake, etc.,

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

CIO Business Intelligence

FEBRUARY 3, 2023

IBM Cloud Pak for Business Automation , for example, provides a low-code studio for testing and developing automation strategies. Teams can iterate over the workflows and explore hypothetical strategies with the Processing Mining tools. Power Advisor tracks statistics about performance to locate bottlenecks and other issues.

Data-driven 145

Data-driven Interactive Enterprise Statistics 145

Depict Data Studio

APRIL 10, 2023

Visualizing data in charts, graphs, dashboards, and infographics is one of the most powerful strategies for getting your numbers out of your spreadsheets and into real-world conversations. and implications of findings) than in statistical significance. But it can be overwhelming to get started with data visualization.

Visualization 105

Visualization Dashboards Testing Reporting 105

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

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