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

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

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. For example, if a stock has a beta of 1.4

Statistics 32

Statistics Uncertainty Risk Marketing 32

DataKitchen

SEPTEMBER 21, 2023

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

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

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

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

CIO Business Intelligence

FEBRUARY 12, 2024

As genAI caught fire in 2023, many organizations rushed to test and learn from the technology and harness it to grow productivity and improve processes. You’ll align desired near-term and future states to test-and-learn pilots as well as potential production projects. High-quality data will be the oil that makes your models hum.

IT 137

IT Consulting Cost-Benefit Uncertainty 137

Jet Global

JANUARY 12, 2021

With the pace of change and uncertainty facing your business, is your current planning process fit for purpose? Discover: How to get started quickly – by turning your existing spreadsheet models into a robust, scalable, and agile planning solution. Webinar Date: February 18, 2021 at 11 AM Local Time. Register Now. Register Now.

Uncertainty 98

Uncertainty Finance Forecasting Testing 98

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

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 157

Metrics KPI Analytics Key Performance Indicator 157

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

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS supports the management, operations, and planning levels of an organization in making better decisions by assessing the significance of uncertainties and the tradeoffs involved in making one decision over another. According to Gartner, the goal is to design, model, align, execute, monitor, and tune decision models and processes.

Data mining 144

Data mining Data-driven Statistics OLAP 144

Cloudera

DECEMBER 3, 2021

Systems should be designed with bias, causality and uncertainty in mind. For example, training an interview screening model using education data often contains gender information. As discussed in this article , model design can also be a source of bias too. Model Drift. System Design. Human Judgement & Oversight.

Uncertainty 102

Uncertainty Measurement Metrics Risk 102

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 107

Metrics Testing Experimentation Modeling 107

CIO Business Intelligence

SEPTEMBER 6, 2023

Today’s business climate is rife with economic uncertainty that is causing IT leaders to do more with less while still innovating to support the business. They also tend to be stable and robust systems owing to thorough vendor testing and years in the market. However, there are some downsides to this ERP approach.

Strategy 105

Strategy Uncertainty Cost-Benefit Optimization 105

CIO Business Intelligence

JANUARY 11, 2024

CIOs are under increasing pressure to deliver AI across their enterprises – a new reality that, despite the hype, requires pragmatic approaches to testing, deploying, and managing the technologies responsibly to help their organizations work faster and smarter. The top brass is paying close attention.

Enterprise 128

Enterprise Uncertainty Reporting Risk Management 128

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

CIO Business Intelligence

JUNE 8, 2022

Digital disruption, global pandemic, geopolitical crises, economic uncertainty — volatility has thrown into question time-honored beliefs about how best to lead IT. Thriving amid uncertainty means staying flexible, he argues. . The coming months are a leadership test for CIOs, and it’s a pass/fail grade.”. Keep calm and lead on.

IT 133

IT Cost-Benefit Uncertainty Digital Transformation 133

CIO Business Intelligence

SEPTEMBER 22, 2022

Seeing that remote working continues to be a pressing issue still finding its footing after nearly three years in beta testing, the work surrounding feasible solutions seems to compound as time goes on, with some intending a full return to office while others have forged the company future on remote models.

Uncertainty 111

Uncertainty Forecasting Visualization Big Data 111

CIO Business Intelligence

AUGUST 1, 2024

The implementation must not become a stalemate for companies: Long legal uncertainty , unclear responsibilities and complex bureaucratic processes in the implementation of the AI Act would hinder European AI innovation. From August 1, 2025, codes of conduct for certain general-purpose AI models will come into force.

Risk 119

Risk Uncertainty Testing Digital Transformation 119

Smart Data Collective

AUGUST 18, 2021

Fortunately, recruitment software and tools allow for data-driven decision-making that eliminates human bias and uncertainties, ultimately helping you make better decisions during the hiring process with greater accuracy and peace of mind. Speed up the recruitment process. Top talent is typically hired by recruiters within ten days.

Data Science 139

Data Science Management Big Data Metrics 139

CIO Business Intelligence

APRIL 22, 2024

Early in this process, I concluded that the previous go-to-market model was too complex and costly for VMware and its customers,” Tan wrote. “It Meanwhile, moving to a subscription pricing model makes sense for both VMware and its customers, Tan wrote. That decision, Cotter says, could drive away potential customers.

Marketing 119

Marketing Uncertainty Strategy Digital Transformation 119

CIO Business Intelligence

FEBRUARY 26, 2024

For any AI model, you can’t interpret the relevance and reliability of the output if you don’t understand the context of the data.” He points to a recent observation from GitHub CEO Thomas Dohmke, who noted 40% of computer-generated code was adopted by developers beta testing its Copilot AI automated code-writing system.

IT 128

IT Uncertainty Strategy Testing 128

CIO Business Intelligence

OCTOBER 8, 2024

The case for a close partnership between data science and business Just in terms of getting off the ground, data scientists bring the skills and mindset to help workflow owners “incorporate unstructured data sources into analyses, translate business problems into analytical models, and understand and explain models’ results.”

Unstructured Data 117

Unstructured Data Data Science Uncertainty Sales 117

Smart Data Collective

FEBRUARY 23, 2022

Many companies are going to have to revamp their entire business models in order to deal with the new technological changes brought on by advances in the IoT. We have many examples of companies that refuse to previous changes in the market and eventually collapse because of their persistent attachment to an old-fashioned business model.

IoT 128

IoT Internet of Things Data-driven Uncertainty 128

CIO Business Intelligence

MAY 24, 2024

During his 53-minute keynote, Nadella showcased updates around most of the company’s offerings, including new large language models (LLMs) , updates to Azure AI Studio , Copilot Studio , Microsoft Fabric , databases offerings , infrastructure , Power Platform , GitHub Copilot , and Microsoft 365 among others.

Uncertainty 111

Uncertainty Enterprise Modeling Software 111

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. That, in turn, led to a slew of manual processes to make descriptive analysis of the test results.

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

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 100

Risk Optimization Management Insurance 100

CIO Business Intelligence

JANUARY 17, 2023

Shut down the testing environment when you’re not using it. For instance, a robust FinOps capability can prevent spend commitment mistakes, and help you switch from a “lift-and-shift” approach founded on a datacenter mentality to a true cloud-centric model that realizes cloud’s full potential. That’s a core benefit of cloud.

Cost-Benefit 138

Cost-Benefit IT Uncertainty Optimization 138

CIO Business Intelligence

AUGUST 26, 2024

In today’s IT landscape, organizations are confronted with the daunting task of managing complex and isolated multicloud infrastructures while being mindful of budget constraints and the need for rapid deployment—all against a backdrop of economic uncertainty and skills shortages.

Management 111

Management Uncertainty Data-driven Software 111

CIO Business Intelligence

SEPTEMBER 13, 2023

Gearing up to build an app that taps the power of highly capable foundation models is not hard for any modern developer. Let them test, learn, and–as the teams individually and collectively build their generative AI knowledge and skills–start playing to win by deploying to prod. CHRO, CMO) as the executive sponsor of one such team.

Uncertainty 105

Uncertainty Interactive Machine Learning Strategy 105

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 119

Software Experimentation Risk Uncertainty 119

IBM Big Data Hub

SEPTEMBER 28, 2023

An AI and data platform, such as watsonx, can help empower businesses to leverage foundation models and accelerate the pace of generative AI adoption across their organization. Business-targeted, IBM-developed foundation models built from sound data Business leaders charged with adopting generative AI need model flexibility and choice.

Testing 87

Testing Finance Enterprise Modeling 87

Jedox

SEPTEMBER 3, 2020

The unprecedented uncertainty forced companies to make critical decisions within compressed time frames. Many pre-crisis business assumptions and planning models became outmoded overnight. Using these drivers as an overlay to stress-test models add robustness to forecasting and can identify exposure and risks to long-term stability.

Uncertainty 81

Uncertainty Forecasting Digital Transformation Risk 81

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

CIO Business Intelligence

MARCH 7, 2023

We’re testing and validating and iterating before we launch these products as generally available.” In a period of great economic uncertainty, enterprises are focusing on customer experience and customer retention, said Gartner distinguished analyst Gene Alvarez. This means customers have choice,” she said.

IT 97

IT Sales Cost-Benefit Interactive 97