The Unofficial Google Data Science Blog

APRIL 19, 2021

by LEE RICHARDSON & TAYLOR POSPISIL Calibrated models make probabilistic predictions that match real world probabilities. To explain, let’s borrow a quote from Nate Silver’s The Signal and the Noise : One of the most important tests of a forecast — I would argue that it is the single most important one — is called calibration.

Modeling 122

Modeling IT Metrics Testing 122

CIO Business Intelligence

NOVEMBER 14, 2022

Decision support systems definition A decision support system (DSS) is an interactive information system that analyzes large volumes of data for informing business decisions. A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. Model-driven DSS.

Data mining 135

Data mining Data-driven Statistics OLAP 135

CIO Business Intelligence

MARCH 7, 2023

We’re testing and validating and iterating before we launch these products as generally available.” It’s easy to see why they’re interested: Generative AI tools such as ChatGPT can write sales proposals or respond interactively to customer complaints far quicker and more cost-effectively than a person.

IT 85

IT Sales Cost-Benefit Interactive 85

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 93

Cost-Benefit Modeling Manufacturing Interactive 93

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. They all serve to answer the question, “How well can my model make predictions based on data?” How can identifying gaps or discrepancies in the training data help you build a more trustworthy model? Dimensions of Trust. How large is the data set?

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

Cloudera

JULY 15, 2021

In this session we explored what firms are doing to approach the uncertainty with more predictability. Pandemic “Pressure” Testing. However, through this real-time “pressure test”, they identified areas of weakness, dependencies, and opportunities. Observe what the model has to offer even if not the intended output.

Risk 99

Risk Optimization Management Insurance 99

O'Reilly on Data

SEPTEMBER 15, 2020

This in turn would increase the platform’s value for users and thus increase engagement, which would result in more eyes to see and interact with ads, which would mean better ROI on ad spend for customers, which would then achieve the goal of increased revenue and customer retention (for business stakeholders).

Cost-Benefit 290

Cost-Benefit Advertising ROI Machine Learning 290

Cloudera

DECEMBER 11, 2020

A recent McKinsey survey, cited in CRN , shows that worldwide, 58 percent of customer interactions were digital as of July 2020. That compares to only 36 percent of customer interactions as of December 2019, which was before the pandemic impacted business, and only 20 percent in May 2018.

Insurance 94

Insurance Digital Transformation Unstructured Data Machine Learning 94

Jet Global

APRIL 22, 2020

Businesses across the globe are facing a level of uncertainty that didn’t exist just months ago. Explore our interactive infographic to reveal valuable insights on how top CFOs are responding from our recent panel discussion, “How to Navigate Your Business Through This Uncertainty.” Brian Shaw. Discovery Education.

Uncertainty 59

Uncertainty Testing Management Modeling 59

CIO Business Intelligence

MAY 6, 2022

Work began in late 2020 on the service, which enables customers to connect through a live video/audio session to a United agent who can, in times of traveler uncertainty and stress, make new reservations on-the-fly, assuage worries about gate changes, and even upgrade the passenger’s seating on their next flight. You see it at the airport.

Uncertainty 96

Uncertainty Testing Digital Transformation Metadata 96

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 138

Risk Manufacturing Enterprise Technology 138

CIO Business Intelligence

JULY 7, 2023

This module validates your ability to measure, assess, and develop the Service Desk practice capability using the ITIL Maturity Model. ITIL Specialist Drive Stakeholder Value : This module covers engagement and interactions among customers, users, suppliers, and partners with the service provider.

Cost-Benefit 98

Cost-Benefit Strategy Management Uncertainty 98

CIO Business Intelligence

JULY 31, 2023

As vendors add generative AI to their enterprise software offerings, and as employees test out the tech, CIOs must advise their colleagues on the pros and cons of gen AI’s use as well as the potential consequences of banning or limiting it. How has, say, ChatGPT hit your business model?” How is your business impacted by generative AI?

Strategy 97

Strategy Risk Enterprise Risk Management 97

The Unofficial Google Data Science Blog

MARCH 31, 2016

KUEHNEL, and ALI NASIRI AMINI In this post, we give a brief introduction to random effects models, and discuss some of their uses. Through simulation we illustrate issues with model fitting techniques that depend on matrix factorization. Random effects models are a useful tool for both exploratory analyses and prediction problems.

Modeling 40

Modeling Statistics Advertising Testing 40

Cloudera

MAY 15, 2018

Over the past decade, we have observed open source powered big data and analytics platforms evolve from large data storage containers to massively scalable advanced modeling platforms that seamlessly operate on-premises and in a multi-cloud environment. Probability, Uncertainty and Quantitative Risk (2017) 2:6. Mauro Cesa. “A

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

Cloudera

NOVEMBER 18, 2021

This allows for an omni-channel view of the customer and enables real-time data streaming and a safe zone to test machine learning models using Cloudera Data Science Workbench (CDSW). The Cloudera technology has also enabled Bank of the West to experiment and scale faster.

Data Lake 76

Data Lake Cost-Benefit Digital Transformation Risk 76

Domino Data Lab

JUNE 23, 2019

As a result, Skomoroch advocates getting “designers and data scientists, machine learning folks together and using real data and prototyping and testing” as quickly as possible. They lack probably what a lot of folks in this room have in terms of domain expertise around data, machine learning, and how these models work. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. 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. Testing out a new feature.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

bridgei2i

JUNE 11, 2020

If nothing else, this anecdote offers valuable insight into the impact that uncertainty of any kind has on consumer behaviour; it triggers volatility. The immediate factor guiding consumer demand behaviour in CPG is Fear— fear of uncertainty, fear of losing incomes, fear of falling sick, fear of running out of essentials etc.

Digital Transformation 52

Digital Transformation Sales Uncertainty Forecasting 52

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 41

Experimentation Statistics Metrics Measurement 41

The Unofficial Google Data Science Blog

APRIL 16, 2019

Modern products often don't start with set-in-stone business models because starting and scaling costs are low. Such decisions involve an actual hypothesis test on specific metrics (e.g. This is a good use of existing experiment infrastructure, but it is not really an experiment as in hypothesis testing.

Experimentation 68

Experimentation Sales Metrics Measurement 68

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

The beliefs of this community are always evolving, and the process of thoughtfully generating, testing, refuting and accepting ideas looks a lot like Science. It is important to make clear distinctions among each of these, and to advance the state of knowledge through concerted observation, modeling and experimentation.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45