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. We must therefore maintain statistical rigor in quantifying experimental uncertainty. In this post we explore how and why we can be “ data-rich but information-poor ”. And an LSOS is awash in data, right?

Experimentation 41

Experimentation Statistics Metrics Measurement 41

AWS Big Data

JANUARY 9, 2024

This functionality was initially released as experimental in OpenSearch Service version 2.4, Hybrid search, the combination of the two methods, gives 14% higher search relevancy (as measured by NDCG@10—a measure of ranking quality) than BM25 alone, so customers want to use hybrid search to get the best of both.

Cost-Benefit 96

Cost-Benefit Visualization Modeling Machine Learning 96

IBM Big Data Hub

MARCH 4, 2024

This culture encourages experimentation and expertise growth. An AI+ enterprise mitigates potential harm by implementing robust measures to secure, monitor and explain AI models, as well as monitoring governance, risk and compliance controls across the hybrid cloud environment.

Enterprise 101

Enterprise ROI Risk Strategy 101

Occam's Razor

APRIL 8, 2013

First, you figure out what you want to improve; then you create an experiment; then you run the experiment; then you measure the results and decide what to do. For each of them, write down the KPI you're measuring, and what that KPI should be for you to consider your efforts a success. Measure and decide what to do.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

IBM Big Data Hub

APRIL 18, 2024

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production.

Cost-Benefit 93

Cost-Benefit Modeling Manufacturing Interactive 93

bridgei2i

APRIL 28, 2020

A three-time recipient of Gartner’s Annual Thought Leadership award, he’s the originator of the field of Infonomics, which is about evaluating and accounting for data or information as an asset. He’s also the man who coined 3Vs- volume, velocity, and variety now commonly used in defining big data. Doug Laney.

Enterprise 103

Enterprise Data Analytics Analytics Forecasting 103

Smart Data Collective

APRIL 23, 2019

Big data is playing a vital role in productivity optimization in virtually every industry. Countless new tools rely on big data to streamline productivity. Big Data Makes Productivity Technology a Thing of the Future. The good news is that new data analytics tools have helped simplify productivity tracking.

Big Data 71

Big Data Measurement Experimentation Reporting 71

The Unofficial Google Data Science Blog

JULY 22, 2020

Instead, we focus on the case where an experimenter has decided to run a full traffic ramp-up experiment and wants to use the data from all of the epochs in the analysis. When there are changing assignment weights and time-based confounders, this complication must be considered either in the analysis or the experimental design.

Experimentation 95

Experimentation Statistics Testing Strategy 95

DataKitchen

APRIL 13, 2021

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix. Azure DevOps.

Testing 300

Testing Machine Learning Consulting Data Quality 300

The Unofficial Google Data Science Blog

JULY 31, 2016

The analysis can be straightforward, especially when it's safe to assume that individual observations of an outcome measure are independent. The outcome measure we care about is an average of the students' test scores, and so the unit of observation is a student. To figure this out, let's consider an appropriate experimental design.

Experimentation 42

Experimentation Testing Measurement Metrics 42

IBM Big Data Hub

OCTOBER 20, 2023

By exploring data from different perspectives with visualizations, you can identify patterns, connections, insights and relationships within that data and quickly understand large amounts of information. AutoAI automates data preparation, model development, feature engineering and hyperparameter optimization.

Machine Learning 75

Machine Learning Manufacturing Cost-Benefit Deep Learning 75

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. These measurement-obsessed companies have an advantage when it comes to AI. Now many people are using Spark.

Management 110

Management Machine Learning Experimentation Metrics 110

datapine

FEBRUARY 4, 2020

Management thinker Peter Drucker once stated, “if you can’t measure it, you can’t improve it” – and he couldn’t be more right. If it has been optimized for SEO though, you shouldn’t stop measuring it after the first week, as it needs a couple of months to reach its “cruising traffic”, and you can get several thousands of monthly visits.

Reporting 280

Reporting Marketing Advertising Metrics 280

Occam's Razor

AUGUST 12, 2013

There are few things more complicated in analytics (all analytics, big data and huge data!) I strongly encourage you to read the post and deeply understand all three and what your marketing and measurement possibilities and limitations are. Test that hypothesis using a percent of your budget and measure results.

Modeling 161

Modeling Optimization Marketing Interactive 161

Domino Data Lab

FEBRUARY 4, 2019

We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.), and dig into details about where science meets rhetoric in data science. That body of work has much to offer the practice of leading data science teams. Taking a pulse.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

Despite a very large number of experimental units, the experiments conducted by LSOS cannot presume statistical significance of all effects they deem practically significant. The result is that experimenters can’t afford to be sloppy about quantifying uncertainty. In statistics, such segments are often called “blocks” or “strata”.

Experimentation 40

Experimentation Metrics Statistics Measurement 40

Occam's Razor

DECEMBER 12, 2016

Digital Marketing & Measurement Model. My solution to this, incredibly real and frustrating problem, is to insist on seeing the signed in blood version of the company's Digital Marketing & Measurement Model. What one critical metric will help you clearly measure performance for each strategy above? That's it.

Analytics 141

Analytics Data-driven Strategy Consulting 141

Cloudera

JUNE 6, 2019

When a mix of batch, interactive, and data serving workloads are added to the mix, the problem becomes nearly intractable. also includes tools for measuring network latency and cross-sectional bandwidth between compute clusters and base clusters to ensure you have an appropriate networking environment for using VPC.

Metadata 85

Metadata Data Lake Optimization Strategy 85

Occam's Razor

FEBRUARY 28, 2017

The qualitative surveys measuring unhappiness went down even more than before. You are what you measure. Bonus: Remember, you can measure profit everyday in Google Analytics! ]. Extend the above incentive purification and imagine the day-to-day behavior of your Acquisition team if you measure them based on CPH.

Key Performance Indicator 106

Key Performance Indicator Metrics Measurement Advertising 106

Occam's Razor

SEPTEMBER 15, 2014

But why blame others, in this post let's focus on one important reason whose responsibility can be squarely put on your shoulders and mine: Measurement. Create a distinct mobile website and mobile app measurement strategies. Media-Mix Modeling/Experimentation. Remember my stress earlier on measuring micro-outcomes?).

Metrics 141

Metrics Reporting Analytics Marketing 141

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

It is important to make clear distinctions among each of these, and to advance the state of knowledge through concerted observation, modeling and experimentation. As you can see from the tiny confidence intervals on the graphs, big data ensured that measurements, even in the finest slices, were precise.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

AWS Big Data

NOVEMBER 14, 2023

With a combination of low-latency data streaming and analytics, they are able to understand and personalize the user experience via a seamlessly integrated, self-reliant system for experimentation and automated feedback. Real-time streaming data technologies are essential for digital transformation.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

Domino Data Lab

MAY 8, 2019

Visualizations are vital in data science work, with the caveat that the information that they convey may be 4-5 layers of abstraction away from the actual business process being measured. measure the subjects’ ability to trust the models’ results. Having more data is generally better; however, there are subtle nuances.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

AWS Big Data

JULY 26, 2023

The vector engine’s compute capacity used for data ingestion, and search and query are measured in OpenSearch Compute Units (OCUs). We recognize that many of you are in the experimentation phase and would like a more economical option for dev-test.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

Occam's Razor

AUGUST 13, 2012

Yehoshua Coren: Best ways to measure user behavior in a multi-touch, multi-device digital world. What's possible to measure. What's not possible to measure. We all have smart phones, laptops, tablets and soon Smart TVs – but most of our measurements are usually done in Cookies that are device/browser specific.

Modeling 124

Modeling Metrics Data Quality Data-driven 124

Occam's Razor

MAY 27, 2015

The content of the letter could be customized to Stephanie's data/behavior. In large measure that is because of the rise of programmatic buying. It is an investment in numerous report writers or data (puking) automation or hiring a small army in India or Philippines to do that, before investing in any smart Analyst.

Marketing Analytics 153

Marketing Analytics Marketing Analytics Advertising 153

Occam's Razor

JANUARY 7, 2014

First… it is important to realize that big data's big imperative is driving big action. Second… well there is no second, it is all about the big action and getting a big impact on your bottom-line from your big investment in analytics processes, consulting, people and tools. . #4:

Data-driven 140

Data-driven Consulting Reporting Marketing 140

DataRobot

APRIL 29, 2021

This list includes: Rachik Laouar is Head of Data Science for the Adecco Group. Rob O’Neill is Head of Analytics for the University Hospitals of Morecambe Bay, NHS Foundation Trust , where he leads teams focused on business intelligence, data science, and information management.

Machine Learning 59

Machine Learning Experimentation Data-driven Data Science 59

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

There is no longer always intentionality behind the act of data collection — data are not collected in response to a hypothesis about the world, but for the same reason George Mallory climbed Everest: because it’s there. Make experimentation cheap and understand the cost of bad decisions. What is to be done?

Experimentation 61

Experimentation Testing Statistics Metrics 61

Occam's Razor

APRIL 29, 2013

It turns out that Marketers, especially Digital Marketers, make really silly mistakes when it comes to data. Small data. Here's why… Real-time data is very expensive. It is expensive from a systems/platforms/data processing/data reporting perspective. Bad ad creatives. Horrible landing pages.

Marketing 166

Marketing Metrics Advertising Measurement 166

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. Years and years of practice with R or "Big Data." There is never a boring moment, there is never time when you can’t do something faster or smarter.

Marketing 136

Marketing Analytics Machine Learning Strategy 136