O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 362

Marketing Experimentation Metrics Testing 362

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. The biggest time sink is often around data collection, labeling and cleaning.

Management 110

Management Machine Learning Experimentation Metrics 110

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. Or something.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Occam's Razor

AUGUST 13, 2012

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. That's simply because this model is unique to my business and my understand of our data. They also reveal things that starting to become scary (Privacy! EU Cookies!)

Modeling 124

Modeling Metrics Data Quality Data-driven 124

Occam's Razor

DECEMBER 12, 2016

Data quality plays a role into this. And, most of the time, regardless of the size of the size of the company, you only know your code is not working post-launch when data is flowing in (not!). with responsibility for every facet of the entire company's data collection, data reporting and data analysis.

Analytics 141

Analytics Data-driven Strategy Consulting 141

datapine

JANUARY 31, 2022

It’s all about using data to get a clearer understanding of reality so that your company can make more strategically sound decisions (instead of relying only on gut instinct or corporate inertia). Ultimately, business intelligence and analytics are about much more than the technology used to gather and analyze data.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214