O'Reilly on Data

APRIL 23, 2024

Google and Amazon were still atop their respective hills of web search and ecommerce in 2010, and Meta’s growth was still accelerating, but it was hard to miss that internet growth had begun to slow. It’s unclear whether this was a lack of imagination or a kind of “ strategy tax.” The market was maturing. I think not.

Advertising 270

Advertising Cost-Benefit Marketing Risk 270

Domino Data Lab

APRIL 3, 2019

Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for Enterprise Repository Era” (1990–2010) – first generation DG solutions. More Policies Emerged” (2010-2018). Andrew Ng later described this strategy as the “Virtuous Cycle of AI” – a.k.a. a second priority?at

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

CIO Business Intelligence

FEBRUARY 26, 2024

This article was co-written by Chris Davis, Partner, Metis Strategy , and Kelley Dougherty, Associate, Metis Strategy To succeed as a large, global company, there is no choice but to harness the power of technology talent around the world.

Cost-Benefit 91

Cost-Benefit Measurement Modeling Strategy 91

O'Reilly on Data

SEPTEMBER 19, 2023

” Each step has been a twist on “what if we could write code to interact with a tamper-resistant ledger in real-time?” ” There’s as much Keras, TensorFlow, and Torch today as there was Hadoop back in 2010-2012. “Here’s our risk model. Those algorithms packaged with scikit-learn?

Machine Learning 247

Machine Learning Testing Modeling Cost-Benefit 247

O'Reilly on Data

JULY 20, 2021

After the release of the iPad in 2010 Craig Hockenberry discussed the great value of communal computing but also the concerns : “When you pass it around, you’re giving everyone who touches it the opportunity to mess with your private life, whether intentionally or not. Remote work changes when and where I should interact with work.

Risk 304

Risk Software Interactive Modeling 304

Occam's Razor

AUGUST 28, 2017

Why the scale at which we can (/have to) solve the problems is already well beyond the grasp of the fundamental strategy most companies follow: We have a bigger revenue opportunity, but we don’t know how to take advantage? The first eye-opening learning for me came from the Google Research team’s post on Learning from Large-Scale Interaction.

Deep Learning 139

Deep Learning Machine Learning Marketing Strategy 139

Occam's Razor

MARCH 23, 2010

For big success you'll need to have a Multiplicity strategy: So when you step back and realize at the minimum you'll also have to use one Voice of Customer tool (for qualitative analysis), one Experimentation tool and (if you want to be great) one Competitive Intelligence tool… do you still want to have two clickstream tools?

Analytics 118

Analytics Consulting Metrics Experimentation 118