O'Reilly on Data

SEPTEMBER 15, 2020

Technical competence results in reduced risk and uncertainty. AI initiatives may also require significant considerations for governance, compliance, ethics, cost, and risk. There’s a lot of overlap between these factors. Defining them precisely isn’t as important as the fact that you need all three. Conclusion.

Advertising 362

Advertising Cost-Benefit ROI Machine Learning 362

O'Reilly on Data

MARCH 25, 2025

People have been building data products and machine learning products for the past couple of decades. The coordination tax: LLM outputs are often evaluated by nontechnical stakeholders (legal, brand, support) not just for functionality, but for tone, appropriateness, and risk. This isnt anything new.

Testing 174

Testing Data-driven Software Measurement 174

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. .

Risk 100

Risk Optimization Management Insurance 100

O'Reilly on Data

JANUARY 22, 2019

They trade the markets using quantitative models based on non-financial theories such as information theory, data science, and machine learning. All models, therefore, need to quantify the uncertainty inherent in their predictions. These factors lead to profound epistemic uncertainty about model parameters.

Modeling 213

Modeling Finance Uncertainty Data mining 213

CIO Business Intelligence

FEBRUARY 20, 2025

In addition, they can use statistical methods, algorithms and machine learning to more easily establish correlations and patterns, and thus make predictions about future developments and scenarios. Most use master data to make daily processes more efficient and to optimize the use of existing resources.

Big Data 84

Big Data Measurement Visualization Machine Learning 84

Rocket-Powered Data Science

JULY 19, 2023

b) Precursor Analytics – the use of AI and machine learning to identify, evaluate, and generate critical early-warning alerts in enterprise systems and business processes, using high-variety data sources to minimize false alarms (i.e., These may not be high risk. They might actually be high-reward discoveries.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

Smart Data Collective

JULY 31, 2022

Predictive analytics tools can be particularly valuable during periods of economic uncertainty. Predictive Analytics Helps Traders Deal with Market Uncertainty. We mentioned that investors can use machine learning to identify potentially profitable IPOs. Analytics Vidhya, Neptune.AI

Predictive Analytics 145

Predictive Analytics Analytics Uncertainty Forecasting 145

O'Reilly on Data

JULY 20, 2021

It comes down to a key question: is the risk associated with an action greater than the trust we have that the person performing the action is who they say they are? When we consider the risk associated with an action, we need to understand its privacy implications. There is a tradeoff between the trust and risk. Source: [link].

Risk 335

Risk Software Interactive Modeling 335

CIO Business Intelligence

MARCH 10, 2023

These, in turn, have brought with them an increase in new threats, risks, and cybercrime. As organizations emerge post-pandemic, many of the risks and uncertainties manifested during that period will persist, including the hybrid workforce, supply chain risk, and other cybersecurity challenges.

Digital Transformation 143

Digital Transformation Cost-Benefit ROI Risk 143

CIO Business Intelligence

NOVEMBER 12, 2024

If your organization is ambivalent about any of these things, you’re at risk of a genAI ROI doom loop, in which people may try very little and quickly run out of ideas. He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing.

ROI 72

ROI Metrics Uncertainty Testing 72

CIO Business Intelligence

JULY 23, 2024

With the confusion about the definition of AI, whether it includes large language models (LLMs), neural networks, machine learning, or simply a data science application, gives companies “a lot of latitude” when claiming to use AI, he says. You run into the fact that these models just don’t behave like your traditional models.

Uncertainty 131

Uncertainty Machine Learning Business Intelligence Marketing 131

CIO Business Intelligence

NOVEMBER 15, 2022

Resilient cybersecurity Despite the clamour for new digital investments, Gartner’s analysts did recognise that this would represent a new cybersecurity risk, with some attributing the increased spending in security over the next year down to ongoing uncertainty regarding Russia’s invasion of Ukraine.

Digital Transformation 143

Digital Transformation Machine Learning Experimentation Metrics 143

DataRobot

AUGUST 5, 2021

After Banjo CEO Damien Patton was exposed as a member of the Ku Klux Klan, including involvement in an anti-Semitic drive-by shooting, the state put the contract on hold and called in the state auditor to check for algorithmic bias and privacy risks in the software. The good news was the software posed less risk to privacy than suspected.

Uncertainty 98

Uncertainty Sales Risk Statistics 98

CIO Business Intelligence

SEPTEMBER 6, 2023

While the potential of Generative AI in software development is exciting, there are still risks and guardrails that need to be considered. Risks of AI in software development Despite Generative AI’s ability to make developers more efficient, it is not error free. To learn more, visit us here.

Software 119

Software Risk Experimentation Uncertainty 119

erwin

AUGUST 13, 2020

managing risk vs ROI and emerging countries)? Technology Disruption : How do we focus on innovation while leveraging existing technology, including artificial intelligence, machine learning, cloud and robotics? Compliance and Legislation : How do we manage uncertainty around legislative change (e.g.,

Enterprise 143

Enterprise Cost-Benefit Uncertainty ROI 143

Cloudera

DECEMBER 3, 2021

Surely there are ways to comb through the data to minimise the risks from spiralling out of control. Systems should be designed with bias, causality and uncertainty in mind. Uncertainty is a measure of our confidence in the predictions made by a system. We need to get to the root of the problem. System Design. Find out more.

Uncertainty 102

Uncertainty Measurement Metrics Risk 102

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. If people need to go through multiple layers of approvals, they run the risk of building a very inefficient system. Tumultuous times redefine what constitutes success.

IT 133

IT Cost-Benefit Uncertainty Digital Transformation 133

Cloudera

DECEMBER 11, 2020

Insurance and finance are two industries that rely on measuring risk with historical data models. To facilitate risk modeling in this new normal, agility and flexibility is required. Finally, he recommends investment in building out a platform that supports the entire machine learning lifecycle to enable the industrialization of ML. .

Insurance 95

Insurance Digital Transformation Unstructured Data Machine Learning 95

Timo Elliott

MARCH 6, 2023

He explains how businesses can leverage AI and machine learning to turn anything into a sensor, detect patterns in new ways, and augment human intelligence. He also mentions ASR Group using machine learning to optimize routes for sugar delivery to their 600 customers, reducing logistics costs.

Machine Learning 111

Machine Learning Cost-Benefit Uncertainty Data Warehouse 111

CIO Business Intelligence

MARCH 25, 2022

Two years of pandemic uncertainty and escalating business risk have sharpened the focus of corporate boards on a technology trend once dismissed as just another IT buzzword. We do this work because of those data benefits: the ability to apply AI or machine learning in ways that drive greater business insights.

Digital Transformation 115

Digital Transformation Machine Learning Uncertainty Strategy 115

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

In conferences and research publications, there is a lot of excitement these days about machine learning methods and forecast automation that can scale across many time series. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast. Forecasting at the “push of a button”?

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. In performance, the trust dimensions are the following: Data quality — the performance of any machine learning model is intimately tied to the data it was trained on and validated against. Dimensions of Trust.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

BizAcuity

MARCH 18, 2019

The consumer lending business is centered on the notion of managing the risk of borrower default. Credit scoring systems and predictive analytics model attempt to quantify uncertainty and provide guidance for identifying, measuring and monitoring risk. Benefits of Predictive Analytics in Unsecured Consumer Loan Industry.

Predictive Analytics 83

Predictive Analytics Analytics Data mining Cost-Benefit 83

Domino Data Lab

JUNE 2, 2019

Secondly, I talked backstage with Michelle, who got into the field by working on machine learning projects, though recently she led data infrastructure supporting data science teams. Just doing machine learning is not enough, and sometimes not even necessary.”. First off, her slides are fantastic! Nick Elprin.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

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. Complaints from dissatisfied customers and apathetic data providers only add to the mounting stress. One of the primary sources of tension? What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

APRIL 28, 2022

Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. Much of this reluctance stems from the regulatory environment, arising from lengthy reviews and approvals processes, or even simple near-term regulatory uncertainty. .

Analytics 98

Analytics Insurance Big Data Uncertainty 98

CIO Business Intelligence

SEPTEMBER 12, 2022

One instance of how that exploration led to real business benefits was with the application of machine learning to predict optimal product formulation using a set of desired consumer benefits. The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says.

Experimentation 133

Experimentation Consulting Technology Machine Learning 133

CIO Business Intelligence

JUNE 25, 2023

For all the risks of hallucinations or bad behavior from models trained on the open internet, generative AI strategy in all our organizations is about unlocking the potential of well-intentioned people to create well-intentioned AIs tailored to their specific context. Artificial Intelligence, Machine Learning

Finance 115

Finance Uncertainty Strategy Modeling 115

CIO Business Intelligence

AUGUST 14, 2023

The objectives were lofty: integrated, scalable, and replicable enterprise management; streamlined business processes; and visualized risk control, among other aims, all fully integrating finance, logistics, production, and sales.

Key Performance Indicator 98

Key Performance Indicator Sales Manufacturing KPI 98

CIO Business Intelligence

OCTOBER 26, 2023

While there is little doubt that companies have been cutting back on expenses generally in response to economic uncertainty, startups in particular have been feeling the pain of contracting budgets and reluctant investors. 10X in 10 Years – can this continue?

IT 128

IT Cost-Benefit Data-driven Manufacturing 128

CIO Business Intelligence

NOVEMBER 27, 2023

That’s not to say they’re looking to ditch their roles or smash machines, as the real Luddites had. Cybersecurity risks This one is no surprise, given the scary statistics on the growing number of cyberattacks, the rate of successful attacks, and the increasingly high consequences of being breached.

IT 138

IT Digital Transformation Reporting Finance 138

CIO Business Intelligence

OCTOBER 8, 2024

Proven reliability is expected–and once it’s achieved, algorithms can operate at machine speed and scale, delivering a lot of value. He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing. But this makes the process much slower by comparison.

Unstructured Data 117

Unstructured Data Data Science Uncertainty Sales 117

Cloudera

OCTOBER 3, 2018

Machine learning brings new challenges, but also transformative power, to our customers. The opportunity has only grown with the advent of practical Internet of Things applications. The tremendous growth in both unstructured and structured data overwhelms traditional data warehouses. We have each innovated separately in those areas.

Uncertainty 75

Uncertainty IoT Risk Reporting 75

Cloudera

SEPTEMBER 29, 2021

In a world rife with uncertainty, governments need to ensure that their citizens’ health and well-being are taken care of even as they seek to keep their economies afloat. Among the use cases for the government organizations that we are working on is one which leverages machine learning to detect fraud in payment systems nationwide.

Digital Transformation 83

Digital Transformation Data Governance Data-driven Machine Learning 83

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). With such an agile response, customers can transact with minimal disruptions and get access to financial services, without putting employees at risk. .

Data Lake 77

Data Lake Cost-Benefit Digital Transformation Risk 77

IBM Big Data Hub

OCTOBER 2, 2023

In a world marked by volatility, uncertainty, complexity, and ambiguity (VUCA) building a holistic planning environment is inevitable for successful steering.” This was done by incorporating mathematical optimization and machine learning algorithms completing the holistic approach for more efficiency.

Analytics 88

Analytics Manufacturing Uncertainty Machine Learning 88