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

Jen Stirrup

NOVEMBER 15, 2022

Therefore, interacting with systems using minimal technical skills is very beneficial. The foundation should be well structured and have essential data quality measures, monitoring and good data engineering practices. Of course, the findings need to add value, but how do we measure this success?

Data Science 145

Data Science Digital Transformation Data-driven Measurement 145

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 95

Insurance Digital Transformation Unstructured Data Machine Learning 95

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 Modeling Manufacturing Interactive 89

Smarten

JULY 18, 2022

The path to Citizen Data Scientist does not have to be fraught with uncertainty.’. The Citizen Data Scientist initiative will improve the accuracy of decisions, and allow users to share data and models with other users, thereby adding value to the organization. Why is it important to implement a Citizen Data Scientist Program?

Uncertainty 52

Uncertainty Predictive Analytics Forecasting Analytics 52

IBM Big Data Hub

OCTOBER 18, 2022

Most admit uncertainty around ROI and nearly half struggle with adequate insights from their data. Fewer than 1 in 4 agree that sustainability requires financial tradeoffs, but many acknowledge the need to redefine and re-calibrate how they measure performance.

Uncertainty 52

Uncertainty Strategy Measurement ROI 52

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 130

Risk Manufacturing Enterprise Technology 130

AWS Big Data

AUGUST 7, 2023

Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future. Amazon Redshift ML makes it easy for data analysts and database developers to create, train, and apply machine learning (ML) models using familiar SQL commands in Amazon Redshift. You pay only the associated Forecast costs.

Forecasting 84

Forecasting Data Warehouse Machine Learning Modeling 84

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 95

Cost-Benefit Strategy Management Uncertainty 95

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 156

Metrics KPI Analytics Key Performance Indicator 156

bridgei2i

JUNE 3, 2020

Consumers feel threatened by the prolonged uncertainty, not having had to deal with anything like it, in their lives. Demand for minimal physical interaction/low human touch products: Due to the risk of infection, customers want to pick up products with minimal human contact.

Manufacturing 52

Manufacturing Forecasting Uncertainty Digital Transformation 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

Domino Data Lab

JUNE 23, 2019

This talk will describe how you can navigate all these challenges that you’re going to face and build a business where every product interaction benefits from your investment in machine learning. These measurement-obsessed companies have an advantage when it comes to AI. All of these people need to get together to make this work.

Management 110

Management Machine Learning Experimentation Metrics 110

Sisense

JULY 29, 2021

The flexible booking model allows users to capture additional revenue from unsold rooms and give them greater ability to pivot as conditions demand. With this cloud-based interactive platform, restaurants can “move past the PDF” and offer real-time interactive menus which are easy to update with price changes and specials.

Insurance 52

Insurance Marketing Uncertainty Reporting 52

bridgei2i

MAY 4, 2020

So the COVID-19 crisis response has hence been centrifugal, and it has varied across countries with respect to infections, control, and lockdown measures. While customer confidence also takes time to recover from rising unemployment, the economic uncertainty, and anxiousness. So the focus here is also to protect lives and livelihoods.

Enterprise 91

Enterprise Digital Transformation Sales Recreation/Entertainment 91

bridgei2i

JULY 8, 2020

This is probably the first time ever that we are witnessing a demand, a supply, and also a resource uncertainty. And if you’re a banker or an insurer, you’re probably busy figuring out how to measure these risks, mobilize these resources, and fund capital that’s going to provide strong growth. These are strange times.

Digital Transformation 132

Digital Transformation Enterprise Insurance Risk 132

Peter James Thomas

AUGUST 12, 2018

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? It is hard to account for such tweaking in measurement systems. Some relate to inherent issues with what is being measured.

Metrics 49

Metrics Statistics Data Quality Measurement 49

CIO Business Intelligence

APRIL 25, 2022

There is a faith embedded in the manifesto that this approach to software engineering is both necessary and superior to older models, such as Waterfall. Does that sound like a methodology that puts “individuals and interactions” over “processes and tools”? Collaboration introduces inevitable uncertainty into the process.

Uncertainty 104

Uncertainty Software Measurement Interactive 104

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. The metrics to measure the impact of the change might not yet be established. It can provide a post hoc measure of eventual impact, and hence insight into what the product might try next. Do you even want those users?

Experimentation 68

Experimentation Sales Metrics Measurement 68

CIO Business Intelligence

APRIL 28, 2024

However, new energy is restricted by weather and climate, which means extreme weather conditions and unpredictable external environments bring an element of uncertainty to new energy sources. We also need to create space for market-oriented interaction. This includes participating in peak regulation according to user market behavior.

Interactive 68

Interactive Uncertainty Data Collection IoT 68

O'Reilly on Data

JULY 20, 2021

When we’re building shared devices with a user model, that model quickly runs into limitations. That model doesn’t fit reality: the identity of a communal device isn’t a single person, but everyone who can interact with it. Remote work changes when and where I should interact with work.

Risk 308

Risk Software Interactive Modeling 308

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. These quasi-explanations usually involve large, real effects and interactions so complex that arguments based on them are often non-falsifiable.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45