The Unofficial Google Data Science Blog

APRIL 23, 2024

Crucially, it takes into account the uncertainty inherent in our experiments. Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. It is a big picture approach, worthy of your consideration.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

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

AWS Big Data

SEPTEMBER 5, 2024

In the context of Retrieval-Augmented Generation (RAG), knowledge retrieval plays a crucial role, because the effectiveness of retrieval directly impacts the maximum potential of large language model (LLM) generation. document-only) ~ 20%(bi-encoder) higher NDCG@10, comparable to the TAS-B dense vector model.

Metrics 111

Metrics Testing Experimentation Modeling 111

CIO Business Intelligence

SEPTEMBER 6, 2023

Since ChatGPT’s release in November of 2022, there have been countless conversations on the impact of similar large language models. The use of AI-generated code is still in an experimental phase for many organizations due to numerous uncertainties such as its impact on security, data privacy, copyright, and more.

Software 120

Software Risk Experimentation Data Lake 120

CIO Business Intelligence

SEPTEMBER 19, 2023

How can enterprises attain these in the face of uncertainty? Rogers: This is one of two fundamental challenges of corporate innovation — managing innovation under high uncertainty and managing innovation far from the core — that I have studied in my work advising companies and try to tackle in my new book The Digital Transformation Roadmap.

Digital Transformation 130

Digital Transformation Uncertainty Testing Enterprise 130

Cloudera

AUGUST 20, 2020

It’s been a year filled with disruption and uncertainty. The company’s advanced AI models can today detect suspicious transactions and rank these transactions with a score so that fraud investigation teams can best prioritise cases that require immediate mitigation — something that’s imperative as business team members work remotely.

Enterprise 121

Enterprise Experimentation Uncertainty Deep Learning 121

CIO Business Intelligence

SEPTEMBER 12, 2022

Prioritize time for experimentation. The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says. It requires bold bets and a willingness to persevere despite setbacks, criticism, and uncertainty,’’ wrote McKinsey senior partners Laura Furstenthal and Erik Roth in a recent blog post. “By

Experimentation 133

Experimentation Consulting Technology Machine Learning 133

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

CIO Business Intelligence

APRIL 6, 2022

If anything, the past few years have shown us the levels of uncertainty we are facing. The race to embrace digital technologies to compete and stay relevant in emerging business models is compelling organizations to shift focus. Approaches like design thinking help empathize with real business problems and customer needs.

Experimentation 104

Experimentation Data Lake Uncertainty Enterprise 104

CIO Business Intelligence

JUNE 28, 2023

These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As Belcorp operates under a direct sales model in 14 countries. Its brands include ésika, L’Bel, and Cyzone, and its products range from skincare and makeup to fragrances.

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

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. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

OCTOBER 18, 2023

If anything, 2023 has proved to be a year of reckoning for businesses, and IT leaders in particular, as they attempt to come to grips with the disruptive potential of this technology — just as debates over the best path forward for AI have accelerated and regulatory uncertainty has cast a longer shadow over its outlook in the wake of these events.

Risk 141

Risk Manufacturing Enterprise Technology 141

CIO Business Intelligence

AUGUST 25, 2023

Where an internal capability does not already exist, and the case relies on a large language model (LLM), you will need to determine how you want to proceed: by training and fine-tuning an off-the-shelf model, like Morgan Stanley did with OpenAI; or by building your own, like Bloomberg did. Experiment. That’s the way you want it.

Strategy 98

Strategy Data Strategy Experimentation Uncertainty 98

Cloudera

OCTOBER 8, 2020

In fact, it was a painful process to overhaul their entire business model and they lost significant revenues over the course of two years. A disruptive mindset creates an environment that embraces constant experimentation and change. Stability during Uncertainty . It was not easy.

Digital Transformation 106

Digital Transformation Unstructured Data Experimentation Uncertainty 106

CIO Business Intelligence

JANUARY 2, 2024

CIOs are readying for another demanding year, anticipating that artificial intelligence, economic uncertainty, business demands, and expectations for ever-increasing levels of speed will all be in play for 2024. He plans to scale his company’s experimental generative AI initiatives “and evolve into an AI-native enterprise” in 2024.

IT 144

IT Cost-Benefit Statistics Consulting 144

DataRobot Blog

OCTOBER 4, 2022

This has prompted AI/ML model owners to retrain their legacy models using data from the post-COVID era, while adapting to continually fluctuating market trends and thinking creatively about forecasting. In the last few years, businesses have experienced disruptions and uncertainty on an unprecedented scale.

Forecasting 59

Forecasting Sales Data-driven Modeling 59

CIO Business Intelligence

JULY 31, 2023

How has, say, ChatGPT hit your business model?” No good guidance yet As CIOs seek to bring control and risk management to technology that’s generating widespread interest and plenty of experimentation, they’re doing so without pre-existing guidance and support. There’s a lot of uncertainty. This is an issue for CIOs.

Strategy 98

Strategy Risk Enterprise Risk Management 98

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

The Unofficial Google Data Science Blog

MAY 31, 2016

A geo experiment is an experiment where the experimental units are defined by geographic regions. The expected precision of our inferences can be computed by simulating possible experimental outcomes. The model regresses the outcomes $y_{1,i}$ on the incremental change in ad spend $delta_i$.

Advertising 43

Advertising Testing Sales Statistics 43

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. Note also that this account does not involve ambiguity due to statistical uncertainty. We sliced and diced the experimental data in many many ways.

Slice and Dice 46

Slice and Dice Experimentation Data-driven Data Science 46

O'Reilly on Data

DECEMBER 9, 2019

Recall from my previous blog post that all financial models are at the mercy of the Trinity of Errors , namely: errors in model specifications, errors in model parameter estimates, and errors resulting from the failure of a model to adapt to structural changes in its environment.

Statistics 32

Statistics Uncertainty Risk Marketing 32

O'Reilly on Data

SEPTEMBER 11, 2019

2 in frequency in proposal topics; a related term, “models,” is No. An ML-related topic, “models,” was No. For example, even though ML and ML-related concepts —a related term, “ML models,” (No. But the database—or, more precisely, the data model —is no longer the sole or, arguably, the primary focus of data engineering.

IoT 25

IoT Big Data Data Warehouse Uncertainty 25

The Unofficial Google Data Science Blog

APRIL 16, 2019

by MICHAEL FORTE Large-scale live experimentation is a big part of online product development. This means a small and growing product has to use experimentation differently and very carefully. This blog post is about experimentation in this regime. But these are not usually amenable to A/B experimentation.

Experimentation 69

Experimentation Sales Metrics Measurement 69

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 42

Experimentation Statistics Metrics Measurement 42

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. At Google, we tend to refer to them as slices.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

CIO Business Intelligence

NOVEMBER 4, 2024

IDC, for instance, recommends the NIST AI Risk Management Framework as a suitable standard to help CIOs develop AI governance in house, as well as EU AI ACT provisions, says Trinidad, who cites best practices for some aspects of AI governance in “ IDC PeerScape: Practices for Securing AI Models and Applications.” The challenges? “AI

Uncertainty 137

Uncertainty Cost-Benefit Risk Experimentation 137

CIO Business Intelligence

APRIL 22, 2025

These core leadership capabilities empower executives to navigate uncertainty, lead with empathy and foster resilience in their organizations. Leaders with high EQ pivot with empathy, adjust in real time and stabilize teams through uncertainty. EQ helps foster teamwork, empathy and resilience.

Technology 99

Technology Uncertainty Experimentation Risk Management 99

CIO Business Intelligence

APRIL 16, 2025

Innovator/experimenter: enterprise architects look for new innovative opportunities to bring into the business and know how to frame and execute experiments to maximize the learnings. Infrastructure architecture: Building the foundational layers of hardware, networking and cloud resources that support the entire technology ecosystem.

Enterprise 124

Enterprise Strategy Risk Business Objectives 124

Timo Elliott

FEBRUARY 7, 2025

Economic uncertainty, geopolitical instability, and the explosion of AI-driven initiatives mean that enterprise architects must redefine their roles to remain relevant and valuable. The Solution: Enterprise architects must redesign their operating models to support federated decision-making.

Enterprise 52

Enterprise IT Digital Transformation Cost-Benefit 52

O'Reilly on Data

APRIL 15, 2025

The most successful teams flip this model by giving domain experts tools to write and iterate on prompts directly. Were making sure the model has the right context to answer questions. Our model suffers from hallucination issues. This prevents your synthetic data from inheriting the biases or limitations of the generating model.

Experimentation 328

Experimentation Testing Metrics Measurement 328