David Menninger's Analyst Perspectives

NOVEMBER 7, 2024

The difference is in using advanced modeling and data management to make faster scenario planning possible, driven by actionable key performance measures that enable faster, well-informed decision cycles. In tech speak, this means the semantic layer is optimized for the intended audience. This may sound like FP&A’s mission today.

Forecasting 130

Forecasting Machine Learning Finance Predictive Analytics 130

AWS Big Data

FEBRUARY 1, 2024

The following are some of the key business use cases that highlight this need: Trade reporting – Since the global financial crisis of 2007–2008, regulators have increased their demands and scrutiny on regulatory reporting.

Data Warehouse 131

Data Warehouse Dashboards Risk Management Risk 131

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning.

Modeling 63

Modeling Experimentation Knowledge Discovery KDD 63

The Unofficial Google Data Science Blog

APRIL 19, 2021

The numerical value of the signal became decoupled from the event it was measuring even as the ordinal value remained unchanged. isn’t good enough: it optimizes the calibration term, but pays the price in sharpness. In practice, we enforce this by optimizing over $log(beta_i)$. And users may start receiving a lot more spam!

Modeling 122

Modeling IT Metrics Testing 122

IBM Big Data Hub

JUNE 1, 2023

The rule proposal would require US publicly traded companies to disclose annually how their businesses are assessing, measuring and managing climate-related risks. This would include disclosure of greenhouse gas emissions as a measure of exposure to climate-related risk.

Risk 56

Risk Reporting Measurement Finance 56

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. It should be noted that inverse probability weighting is not generally optimal (i.e., the curse of dimensionality).

Statistics 45

Statistics Optimization Modeling Experimentation 45

The Unofficial Google Data Science Blog

JULY 22, 2020

For this reason we don’t report uncertainty measures or statistical significance in the results of the simulation. Ramp-up solution: measure epoch and condition on its effect If one wants to do full traffic ramp-up and use data from all epochs, they must use an adjusted estimator to get an unbiased estimate of the average reward in each arm.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

Occam's Razor

MARCH 12, 2012

All the way back in 2007, I was evangelizing the value of moving away from the "small data" world of clickstream data to the "bigger data" world of using multiple data sources to make smarter decisions on the web. Here's the "bigger web analytics data" picture from 2007… Multiplicity!

Big Data 128

Big Data Data-driven Unstructured Data Marketing 128

Occam's Razor

AUGUST 22, 2011

Key To Your Digital Success: Web Analytics Measurement Model. " Measuring Incrementality: Controlled Experiments to the Rescue! Barriers To An Effective Web Measurement Strategy [+ Solutions!]. Measuring Online Engagement: What Role Does Web Analytics Play? "Engagement" How Do I Measure Success?

KPI 125

KPI Metrics Measurement ROI 125

Occam's Razor

FEBRUARY 7, 2011

Brian Krick: Best way to measure and communicate "available demand" from available channels (social, search, display) for forecast modeling. Additionally, it is exceptionally difficult to measure available demand because 1. Alex Cohen: How to optimize with sparse data! No accountability = very little desire to measure.

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

Occam's Razor

OCTOBER 15, 2012

I spend 70% of my time in the US and for those discussions I'm primary looking at speed (connection above), mobile penetration (yes, 2007 was the year of mobile!), It is SUPER important to passionately measure the offline impact of your online efforts until the day you die (cue, dramatic music). It is an intense amount of effort.

Advertising 137

Advertising Marketing Strategy Insurance 137

Edwin Chen

MARCH 13, 2011

This is a summary of Bell and Koren’s 2007 Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights paper. We’ll see how using an optimization method to derive weights (as opposed to deriving weights via a similarity function) overcomes these two limitations.

Optimization 40

Optimization Modeling Cost-Benefit Measurement 40

Domino Data Lab

FEBRUARY 4, 2019

The ability to measure results (risk-reducing evidence). Frédéric Kaplan, Pierre-Yves Oudeyer (2007). Oudeyer and Twomey separately describe processes for curiosity-driven exploration which have parallels in A* search and heuristic optimizations for gradient descent. You’ll need to read the papers.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

CIO Business Intelligence

OCTOBER 29, 2024

since 2007. EA’s look at the entire “estate” with an enterprise-wide view and being inclusive in their approach to solutioning business asks while acknowledging the importance of taking sustainability measures and responsible AI practices into account. Measures progress in reducing outdated or redundant technology systems.

Enterprise 122

Enterprise Cost-Benefit Metrics Strategy 122