Occam's Razor

AUGUST 12, 2013

than multi-channel attribution modeling. By the time you are done with this post you'll have complete knowledge of what's ugly and bad when it comes to attribution modeling. You'll know how to use the good model, even if it is far from perfect. Multi-Channel Attribution Models. Linear Attribution Model.

Modeling 162

Modeling Optimization Marketing Interactive 162

O'Reilly on Data

SEPTEMBER 15, 2020

In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. Technical sophistication: Sophistication measures a team’s ability to use advanced tools and techniques (e.g., PyTorch, TensorFlow, reinforcement learning, self-supervised learning).

Advertising 362

Advertising Cost-Benefit ROI Machine Learning 362

CIO Business Intelligence

JANUARY 21, 2025

Deloittes State of Generative AI in the Enterprise reports nearly 70% have moved 30% or fewer of their gen AI experiments into production, and 41% of organizations have struggled to define and measure the impacts of their gen AI efforts. Even this breakdown leaves out data management, engineering, and security functions.

Cost-Benefit 142

Cost-Benefit Data-driven Strategy Marketing 142

Occam's Razor

SEPTEMBER 19, 2011

How do you get over the frustration of having done attribution modeling and realizing that it is not even remotely the solution to your challenge of using multiple media channels? We'll measure Revenue, Profit (the money we make less cost of goods sold), Expense (cost of campaign), Net (bottom-line impact). ask for a raise.

Measurement 120

Measurement Advertising Testing Marketing 120

DataKitchen

JANUARY 20, 2021

Centralizing analytics helps the organization standardize enterprise-wide measurements and metrics. Central DataOps process measurement function with reports. The center of excellence (COE) model leverages the DataOps team to solve real-world challenges. DataOps Center of Excellence.

Metrics 243

Metrics Experimentation Measurement Testing 243

CIO Business Intelligence

MARCH 5, 2025

Two years of experimentation may have given rise to several valuable use cases for gen AI , but during the same period, IT leaders have also learned that the new, fast-evolving technology isnt something to jump into blindly. The next thing is to make sure they have an objective way of testing the outcome and measuring success.

Testing 99

Testing Measurement Technology Experimentation 99

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”.

Management 314

Management Machine Learning Metrics Modeling 314

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. DataOps requires that teams measure their analytic processes in order to see how they are improving over time. Datatron — Automates deployment and monitoring of AI models.

Testing 300

Testing Machine Learning Consulting Data Science 300

Occam's Razor

AUGUST 13, 2012

Yehoshua Coren: Best ways to measure user behavior in a multi-touch, multi-device digital world. Yehoshua I've covered this topic in detail in this blog post: Multi-Channel Attribution: Definitions, Models and a Reality Check. What's possible to measure. What's not possible to measure. Let's do this!

Modeling 125

Modeling Metrics Data Quality Data-driven 125

AWS Big Data

JANUARY 15, 2025

EUROGATEs data science team aims to create machine learning models that integrate key data sources from various AWS accounts, allowing for training and deployment across different container terminals. Insights from ML models can be channeled through Amazon DataZone to inform internal key decision makers internally and external partners.

IoT 101

IoT Machine Learning Metadata Data-driven 101

O'Reilly on Data

MARCH 23, 2023

It’s important to understand that ChatGPT is not actually a language model. It’s a convenient user interface built around one specific language model, GPT-3.5, is one of a class of language models that are sometimes called “large language models” (LLMs)—though that term isn’t very helpful. with specialized training.

IT 348

IT Modeling Testing Risk 348

Corinium

JUNE 6, 2019

Beyond that, we recommend setting up the appropriate data management and engineering framework including infrastructure, harmonization, governance, toolset strategy, automation, and operating model. It is also important to have a strong test and learn culture to encourage rapid experimentation.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

CIO Business Intelligence

AUGUST 20, 2024

Our mental models of what constitutes a high-performance team have evolved considerably over the past five years. Post-pandemic, high-performance teams excelled at remote and hybrid working models, were more empathetic to individual needs, and leveraged automation to reduce manual work.

IT 141

IT Digital Transformation Experimentation Risk 141

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Occam's Razor

APRIL 8, 2013

Let's listen in as Alistair discusses the lean analytics model… The Lean Analytics Cycle is a simple, four-step process that shows you how to improve a part of your business. Another way to find the metric you want to change is to look at your business model. The business model also tells you what the metric should be.

Metrics 157

Metrics KPI Analytics Key Performance Indicator 157

IBM Big Data Hub

MAY 17, 2024

Cloud maturity models are a useful tool for addressing these concerns, grounding organizational cloud strategy and proceeding confidently in cloud adoption with a plan. Cloud maturity models (or CMMs) are frameworks for evaluating an organization’s cloud adoption readiness on both a macro and individual service level.

Modeling 96

Modeling Cost-Benefit Optimization Digital Transformation 96

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. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

Modeling 63

Modeling Experimentation Knowledge Discovery Testing 63

Rocket-Powered Data Science

JULY 7, 2019

Autonomous Vehicles: Self-driving (guided without a human), informed by data streaming from many sensors (cameras, radar, LIDAR), and makes decisions and actions based on computer vision algorithms (ML and AI models for people, things, traffic signs,…). Examples: Cars, Trucks, Taxis. See [link]. Industry 4.0 2) Connected cars. (3)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

CIO Business Intelligence

MAY 1, 2024

Gen AI takes us from single-use models of machine learning (ML) to AI tools that promise to be a platform with uses in many areas, but you still need to validate they’re appropriate for the problems you want solved, and that your users know how to use gen AI effectively. Pilots can offer value beyond just experimentation, of course.

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

CIO Business Intelligence

JUNE 13, 2024

Proof that even the most rigid of organizations are willing to explore generative AI arrived this week when the US Department of the Air Force (DAF) launched an experimental initiative aimed at Guardians, Airmen, civilian employees, and contractors. It is not training the model, nor are responses refined based on any user inputs.

Testing 119

Testing Experimentation Data Processing Modeling 119

CIO Business Intelligence

SEPTEMBER 12, 2024

Unmonitored AI tools can lead to decisions or actions that undermine regulatory and corporate compliance measures, particularly in sectors where data handling and processing are tightly regulated, such as finance and healthcare. Generative AI models can perpetuate and amplify biases in training data when constructing output.

Experimentation 111

Experimentation Risk Cost-Benefit Strategy 111

Domino Data Lab

NOVEMBER 14, 2019

Model interpretability continues to spark public discourse among industry. We have covered model interpretability previously, including a proposed definition of machine learning (ML) interpretability. Yet there are tradeoffs to consider when selecting a model. Errors like these may occur when the model is being constructed.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

CIO Business Intelligence

JUNE 14, 2023

Certifications measure your knowledge and skills against industry- and vendor-specific benchmarks to prove to employers that you have the right skillset. They can also transform the data, create data models, visualize data, and share assets by using Power BI. The number of data analytics certs is expanding rapidly.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

CIO Business Intelligence

AUGUST 15, 2024

When we do planning sessions with our clients, two thirds of the solutions they need don’t necessarily fit the generative AI model. However, foundational models will always have a place as the core backbone for the industry.” “There are a lot of cool AI solutions that are cheaper than generative AI,” Stephenson says.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

Occam's Razor

JULY 18, 2011

The only requirement is that your mental model (and indeed, company culture) should be solidly rooted in permission marketing. You just have to have the right mental model (see Seth Godin above) and you have to… wait for it… wait for it… measure everything you do! Just to ensure you are executing against your right mental model.

Metrics 138

Metrics Marketing Measurement Cost-Benefit 138

CIO Business Intelligence

DECEMBER 11, 2024

Research from IDC predicts that we will move from the experimentation phase, the GenAI scramble that we saw in 2023 and 2024, and mature into the adoption phase in 2025/26 before moving into AI-fuelled businesses in 2027 and beyond. So what are the leaders doing differently?

ROI 59

ROI Experimentation Insurance Strategy 59

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 96

Experimentation Statistics Testing Knowledge Discovery 96

CIO Business Intelligence

FEBRUARY 1, 2024

Prioritising and measuring is key Generative AI represents a welcome shot in the arm for a sector in desperate need of efficiency and productivity gains. In the short term, healthcare CIOs need to focus on prioritising their use cases and ensuring they have a robust measuring framework in place to assess the results of trial deployment.

Experimentation 115

Experimentation Forecasting Measurement Cost-Benefit 115

CIO Business Intelligence

JANUARY 28, 2025

This transition represents more than just a shift from traditional systemsit marks a significant pivot from experimentation and proof-of-concept to scaled adoption and measurable value.

Digital Transformation 52

Digital Transformation Data-driven Experimentation Strategy 52

CIO Business Intelligence

JULY 1, 2024

Notable examples of AI safety incidents include: Trading algorithms causing market “flash crashes” ; Facial recognition systems leading to wrongful arrests ; Autonomous vehicle accidents ; AI models providing harmful or misleading information through social media channels.

Reporting 129

Reporting Risk Management Experimentation Risk 129

Smart Data Collective

FEBRUARY 4, 2020

Current R&D Models Provide Diminishing Returns. The greatest advantage of AI is that it can digest vast amounts of medical knowledge — from thousands of published reports and scientific papers, say — and devise novel predictions and formulations that would take human researchers years of inefficient experimentation to find.

Experimentation 115

Experimentation Testing Modeling Strategy 115

CIO Business Intelligence

AUGUST 23, 2024

Data scientists at Bayer have developed several proofs of concept of generative AI models on the new platform that remain in discovery and evaluation phase for “efficacy,” McQueen says, adding that the models won’t be in production until 2025. The R&D pipeline is pretty highly confidential at this point,” he says. It’s additive.”

Data Science 101

Data Science Experimentation Testing Modeling 101

CIO Business Intelligence

AUGUST 14, 2024

It’s embedded in the applications we use every day and the security model overall is pretty airtight. Microsoft has also made investments beyond OpenAI, for example in Mistral and Meta’s LLAMA models, in its own small language models like Phi, and by partnering with providers like Cohere, Hugging Face, and Nvidia. That’s risky.”

Enterprise 136

Enterprise Cost-Benefit Experimentation Modeling 136

CIO Business Intelligence

JULY 8, 2022

After transforming their organization’s operating model, realigning teams to products rather than to projects , CIOs we consult arrive at an inevitable question: “What next?” Splitting these responsibilities without a clear vision and careful plan, however, can spell disaster, reversing the progress begotten by a new operating model.

Cost-Benefit 122

Cost-Benefit Measurement Modeling Metrics 122

CIO Business Intelligence

NOVEMBER 13, 2023

Foster a culture of innovation: Digital transformation requires innovation and experimentation, and thus a culture for embracing new technologies and ideas. Leaders must clearly define what they want to achieve through digital transformation and how they plan to do it. Digital Transformation, IT Leadership, IT Strategy

Digital Transformation 143

Digital Transformation Cost-Benefit Experimentation Measurement 143

CIO Business Intelligence

JULY 7, 2023

Tip 1: Embrace the need for balance Hybrid work models have shifted the goalposts for just about all organizational objectives, especially in terms of providing employee experiences that are both productive and secure. They are expected to make smarter and faster decisions using data, analytics, and machine learning models.

Measurement 122

Measurement Risk Experimentation Enterprise 122