The Data Visualisation Catalogue

OCTOBER 18, 2024

A Fan Chart is a visualisation tool used in time series analysis to display forecasts and associated uncertainties. Each shaded area shows the range of possible future outcomes and represents different levels of uncertainty with the darker shades indicating higher levels of probability.

Snapshot 84

Snapshot Uncertainty Forecasting Risk 84

O'Reilly on Data

MARCH 25, 2025

Throughout this article, well explore real-world examples of LLM application development and then consolidate what weve learned into a set of first principlescovering areas like nondeterminism, evaluation approaches, and iteration cyclesthat can guide your work regardless of which models or frameworks you choose. Which multiagent frameworks?

Testing 168

Testing Data-driven Software Measurement 168

Jedox

APRIL 16, 2020

Dean Boyer as a guest to the Jedox Blog for our series on “Managing Uncertainty” Mr. Boyer is a Director of Technology Services at Marks Paneth LLP, a premier accounting firm based in the United States. He shares his expertise on how an EPM solution supports managing economic uncertainty, particularly in times of crisis.

Uncertainty 94

Uncertainty Management Forecasting Predictive Modeling 94

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. Machine learning adds uncertainty. Models also become stale and outdated over time.

Management 363

Management Machine Learning Experimentation Metrics 363

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities. So, if you have 1 trillion data points (g.,

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

NOVEMBER 18, 2024

Data silos, lack of standardization, and uncertainty over compliance with privacy regulations can limit accessibility and compromise data quality, but modern data management can overcome those challenges. Some of the key applications of modern data management are to assess quality, identify gaps, and organize data for AI model building.

Data-driven 111

Data-driven Machine Learning ROI Uncertainty 111

CIO Business Intelligence

OCTOBER 11, 2024

These language models contain an incredible amount of knowledge, and if you need to know more in a specific area, you can use the tool to build knowledge,” he says. It’s a factor of uncertainty and difficult to see how models develop and the functionality of the tools.” Another is research.

Uncertainty 126

Uncertainty Testing Technology Modeling 126

CIO Business Intelligence

AUGUST 24, 2023

It’s no surprise, then, that according to a June KPMG survey, uncertainty about the regulatory environment was the top barrier to implementing gen AI. So here are some of the strategies organizations are using to deploy gen AI in the face of regulatory uncertainty. Companies in general are still having problems with data governance.”

Uncertainty 98

Uncertainty Risk Testing Enterprise 98

Andrew White

MAY 4, 2020

COVID-19 and the related economic fallout has pushed organizations to extreme cost optimization decision making with uncertainty. In the realm of AI and Machine Leaning, data is used to train models to help explore specific business issues or questions. The models are practically useless. Everything Changes.

Uncertainty 90

Uncertainty Data Quality Consulting Predictive Modeling 90

CIO Business Intelligence

DECEMBER 1, 2023

Saving money is a top priority for many organizations, particularly during periods of economic uncertainty. Yesterday’s hub-and-spoke networks and castle-and-moat security models were adequate when users, applications, and data all resided onsite in the corporate office or data center.

Uncertainty 98

Uncertainty ROI Dashboards Modeling 98

Smart Data Collective

MARCH 2, 2023

As a result, they will need to invest in data analytics tools to sustain a competitive edge in the face of growing economic uncertainty. Therefore, it is a good idea to have predictive analytics models that account for these variables. However, there are even more important benefits of using big data during a bad economy.

Big Data 105

Big Data Uncertainty Risk Data mining 105

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 competence results in reduced risk and uncertainty. Outputs from trained AI models include numbers (continuous or discrete), categories or classes (e.g.,

Advertising 362

Advertising Cost-Benefit ROI Machine Learning 362

O'Reilly on Data

JUNE 15, 2023

The world changed on November 30, 2022 as surely as it did on August 12, 1908 when the first Model T left the Ford assembly line. The creators of generative AI systems and Large Language Models already have tools for monitoring, modifying, and optimizing them. Would such a pause have made us better or worse off?

Metrics 359

Metrics Reporting Measurement Finance 359

CIO Business Intelligence

DECEMBER 20, 2022

In the coming year, having a good read on customer needs will be crucial as many organizations battle resource constraints, challenging economic conditions, and continuing uncertainty when it comes to planning.

Uncertainty 98

Uncertainty Digital Transformation Optimization Data Science 98

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

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 308

Management Machine Learning Metrics Modeling 308

CIO Business Intelligence

NOVEMBER 1, 2024

One of the firm’s recent reports, “Political Risks of 2024,” for instance, highlights AI’s capacity for misinformation and disinformation in electoral politics, something every client must weather to navigate their business through uncertainty, especially given the possibility of “electoral violence.” “The

IT 122

IT Insurance Consulting Risk 122

The Unofficial Google Data Science Blog

APRIL 19, 2021

by LEE RICHARDSON & TAYLOR POSPISIL Calibrated models make probabilistic predictions that match real world probabilities. While calibration seems like a straightforward and perhaps trivial property, miscalibrated models are actually quite common. Why calibration matters What are the consequences of miscalibrated models?

Modeling 122

Modeling IT Metrics Testing 122

CIO Business Intelligence

NOVEMBER 1, 2024

One of the firm’s recent reports, “Political Risks of 2024,” for instance, highlights AI’s capacity for misinformation and disinformation in electoral politics, something every client must weather to navigate their business through uncertainty, especially given the possibility of “electoral violence.” “The

IT 105

IT Insurance Consulting Risk 105

CIO Business Intelligence

JULY 18, 2022

According to John-David Lovelock, research vice president at Gartner, inflationary pressures are top-of-mind for most IT decision-makers at the moment, which creates a degree of uncertainty—high prices today could become even higher tomorrow. in 2022, according to Gartner.

IT 144

IT Uncertainty Data-driven Sales 144

CIO Business Intelligence

APRIL 11, 2023

Over the next five years, the healthcare industry is expected to go through dramatic changes as service providers expand value-based care models and equipment manufacturers strive to keep pace in a digital-first world. Betadam: I think there is definitely a slowdown in innovation activities, especially during times of economic uncertainty.

Modeling 98

Modeling IT Strategy Uncertainty 98

CIO Business Intelligence

DECEMBER 5, 2024

AI faces a fundamental trust challenge due to uncertainty over safety, reliability, transparency, bias, and ethics. As part of its model, SAS has an AI Oversight committee that might reject a generative AI marketing message as inappropriate, for example.

Cost-Benefit 59

Cost-Benefit Uncertainty Marketing Risk 59

DataRobot

AUGUST 5, 2021

AI and Uncertainty. Some people react to the uncertainty with fear and suspicion. Recently published research addressed the question of “ When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making.”. People are unsure about AI because it’s new. AI you can trust.

Uncertainty 98

Uncertainty Sales Risk Statistics 98

CIO Business Intelligence

AUGUST 15, 2024

For instance, the increasing cost of capital has affected access to and use of money across all sectors; an increasing regulatory focus on competition and industry dynamics has driven increased scrutiny as a critical factor for uncertainty; geopolitical uncertainties, including unprecedented conflicts across many regions, have forced delays.

Uncertainty 111

Uncertainty Risk Strategy Cost-Benefit 111

Rocket-Powered Data Science

MAY 21, 2024

Another example is Pure Storage’s FlashBlade ® which was invented to help companies handle the rapidly increasing amount of unstructured data coming into greater use, as required in the training of multi-modal AI models. In deep learning applications (including GenAI, LLMs, and computer vision), a data object (e.g.,

Cost-Benefit 239

Cost-Benefit Unstructured Data Enterprise Technology 239

CIO Business Intelligence

JULY 23, 2024

It’s, ‘We’ve seen the power of OpenAI—tell me how we’re going to be using large language models in order to transform our business.’” Gen AI can still hallucinate, even if tuned, creating a level of uncertainty when more traditional tools would be more consistent.

Uncertainty 131

Uncertainty Machine Learning Business Intelligence Marketing 131

Cloudera

JUNE 1, 2021

It also means we can complete our business transformation with the systems, processes and people that support a new operating model. . Cazena’s platform includes end-to-end SaaS orchestration, so customers get a fully-managed operations model that delivers guaranteed security and performance 24×7. Our strategy.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

CIO Business Intelligence

JANUARY 11, 2024

To get back in front, IT leaders will have to transform lessons learned from 2023 into actionable, adaptable processes, as veteran technology pros have been remarkably consistent in identifying global and economic uncertainties as key challenges for IT leaders to anticipate in 2024 as well.

IT 133

IT Uncertainty Cost-Benefit Strategy 133

O'Reilly on Data

SEPTEMBER 15, 2021

There was a lot of uncertainty about stability, particularly at smaller companies: Would the company’s business model continue to be effective? Economic uncertainty caused by the pandemic may be responsible for the declines in compensation. Would your job still be there in a year? Think about it.”

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

CIO Business Intelligence

SEPTEMBER 2, 2022

The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. So far, we have deployed roughly 71 models with a clear operating income and impact on the business. I imagine these models have a direct impact on the customer experience. Khare: Yes, they do.

Uncertainty 98

Uncertainty Manufacturing Data-driven Business Intelligence 98

CIO Business Intelligence

SEPTEMBER 2, 2022

The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. So far, we have deployed roughly 71 models with a clear operating income and impact on the business. I imagine these models have a direct impact on the customer experience. Khare: Yes, they do.

Uncertainty 98

Uncertainty Manufacturing Data-driven Business Intelligence 98

CIO Business Intelligence

SEPTEMBER 15, 2023

In August, Salesforce released a new no-code , interface-based AI and generative AI model training tool, dubbed Einstein Studio , as part of its Data Cloud offering. The new hires, according to Millham, will be divided between sales, engineering, and the team handling the development of its Data Cloud.

IT 132

IT Uncertainty Sales Data-driven 132

Domino Data Lab

MARCH 21, 2023

98% of CDOs and CDAOs say the companies that bring AI and ML solutions to market fastest will be the ones who survive and thrive in the upcoming times of economic uncertainty. In today's economic environment, all organizations need to unlock greater AI value, faster.

Uncertainty 98

Uncertainty Enterprise Marketing Modeling 98

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

Others argue that there will still be a unique role for the data scientist to deal with ambiguous objectives, messy data, and knowing the limits of any given model. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast.

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

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. With enough data, models can be created to “read between the lines” in both helpful and dangerous ways.

Risk 331

Risk Software Interactive Modeling 331

Domino Data Lab

MAY 15, 2019

Unfortunately, a common challenge that many industry people face includes battling “ the model myth ,” or the perception that because their work includes code and data, their work “should” be treated like software engineering. This work includes model improvements as well as adding new signals and features into the model.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111