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

DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses.

Risk 111

Risk Modeling IT Risk Management 111

O'Reilly on Data

SEPTEMBER 19, 2023

They’d grown tired of learning what is; now they wanted to know what’s next. Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. It felt like, almost overnight, all of machine learning took on some kind of neural backend. “Here’s our risk model.

Machine Learning 339

Machine Learning Testing Modeling Cost-Benefit 339

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. pharmacogenomics) and risk assessment of genetic disorders (e.g., Machine Learning and Predictive Modeling of Customer Churn.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning? temperature, salary).

Machine Learning 73

Machine Learning Modeling Deep Learning Predictive Modeling 73

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Financial services: Develop credit risk models.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

Rocket-Powered Data Science

OCTOBER 6, 2023

In these applications, the data science involvement includes both the “learning” of the most significant patterns to alert on and the improvement of their models (logic) to minimize false positives and false negatives. Broken models are definitely disruptive to analytics applications and business operations.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Statistics 157

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. With the exponential growth of large datasets, predictive analytics is being leveraged by enterprises across industries.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. How Machine Learning Helps Detect and Prevent AML. Predictive Analytics can help businesses in reducing risk (eg.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

DataRobot Blog

JULY 22, 2022

At many organizations, the current framework focuses on the validation and testing of new models, but risk managers and regulators are coming to realize that what happens after model deployment is at least as important. Legacy Models. No predictive model — no matter how well-conceived and built — will work forever.

Modeling 105

Modeling Risk Management Testing Machine Learning 105

datapine

DECEMBER 4, 2019

Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

DataKitchen

SEPTEMBER 21, 2023

This proactive approach to data quality guarantees that downstream analytics and business decisions are based on reliable, high-quality data, thereby mitigating the risks associated with poor data quality. There are multiple locations where problems can happen in a data and analytic system. What is Data in Use?

Testing 173

Testing Data Quality Predictive Modeling Metrics 173

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Smarten

SEPTEMBER 14, 2018

Just Simple, Assisted Predictive Modeling for Every Business User! You can’t get a business loan, join with a business partner, successfully bid on a project, open a new location, hire the right employees or plan for the future without predictive analytics. No Guesswork!

Predictive Modeling 40

Predictive Modeling Business Analytics Modeling Analytics 40

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

CIO Business Intelligence

MAY 9, 2024

Companies want candidates who can drive innovation, deliver meaningful business results, and work closely with other leaders to manage risks. And they must develop and upskill talent to ensure the workforce is well-versed in the innovation and risk associated with AI use. The same can be said for AI talent in general, Daly stresses.

Risk Management 138

Risk Management Cost-Benefit Risk Technology 138

IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 70

Risk Modeling Management Metadata 70

Cloudera

JULY 18, 2018

It is fair to say that healthcare faces many challenges, including developing, deploying, and integrating machine learning and artificial intelligence (AI) into clinical workflow and care delivery. Actionable healthcare analytics that allows organizations to conduct real-time “what if scenarios” against predictive models.

Machine Learning 51

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 51

Smart Data Collective

MAY 17, 2021

Big data solutions are often created and supported using various technologies from IIoT to machine learning and AI. All that performance data can be fed into a machine learning tool specifically designed to identify certain events, failures or obstacles. It also introduces operational efficiencies.

Big Data 132

Big Data Cost-Benefit IoT Machine Learning 132

CIO Business Intelligence

JUNE 7, 2022

Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. In business, predictive analytics uses machine learning, business rules, and algorithms.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

DataRobot

JANUARY 20, 2022

Through the use of real-time datasets, machine learning, and wide-ranging AI capabilities, stakeholders across the enterprise including executives, clinicians, operational managers, and analysts will become more empowered to make forward-looking decisions faster. . – Public sector data sharing. Grasping the digital opportunity.

Data-driven 145

Data-driven Experimentation Predictive Modeling Data Warehouse 145

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029. Many stock market transactions use ML.

Machine Learning 48

Machine Learning Marketing Forecasting Modeling 48

David Menninger's Analyst Perspectives

NOVEMBER 7, 2024

Predictive analytics applies machine learning to statistical modeling and historical data to make predictions about future outcomes. By identifying patterns and trends in past data, predictive analytics helps businesses forecast future events, assess risks, and uncover opportunities.

Forecasting 130

Forecasting Machine Learning Finance Predictive Analytics 130

CIO Business Intelligence

AUGUST 23, 2023

To do so, they explored the optimization problem of “cardinality constraints” and developed a hybrid quantum-classical approach to financial index tracking portfolios that maximizes returns and minimizes risk. We started our models, pressed run, and had to wait until the morning and hope they hadn’t crashed overnight,” Broer says.

IT 97

IT Machine Learning Risk Optimization 97

CIO Business Intelligence

MARCH 22, 2023

Enter the new class ML data scientists require large quantities of data to train machine learning models. Then the trained models become consumers of vast amounts of data to gain insights to inform business decisions. It is often used to train machine learning models and protect sensitive data in healthcare and finance.

Machine Learning 105

Machine Learning Cost-Benefit Modeling Risk 105

CIO Business Intelligence

OCTOBER 5, 2023

As chief digital and technology officer at CBRE, Davé recognized early that the commercial real estate industry was ripe for AI and machine learning enhancements, and he and his team have tested countless use cases across the enterprise ever since. For AI, the high-value quadrant is where you’ll find most predictive modeling.

Experimentation 130

Experimentation Strategy Machine Learning Interactive 130

DataRobot Blog

JUNE 3, 2022

Generative Pre-trained Transformer 3 (GPT-3) is a language model that utilizes deep-structured learning to predict human-like text. GPT-3 was created by OpenAI – a San Francisco-based artificial intelligence research laboratory – as the third-generation language prediction model in the GPT-n series. Download now.

Risk 52

Risk Predictive Modeling Modeling Machine Learning 52

CIO Business Intelligence

JUNE 22, 2022

The financial services industry has had to dedicate more resources to personalisation, fighting fraud, and reducing cloud concentration risk. Real-time access to accurate data on customers that drives machine learning models are crucial to the accuracy of predictions or recommendations they make in real time.

IoT 98

IoT IT Manufacturing Internet of Things 98

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. Finances: can Iower financial risk? Usage in a business context.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

Cloudera

NOVEMBER 18, 2020

With this functionality, business units can now leverage big data analytics to develop better and faster insights to help achieve better revenues, higher productivity, and decrease risk. . The pipeline provides its clinicians fast access to real-time patient data and prediction models. Data Champions . Winner: OVO.

Internet Publishing and Broadcasting 123

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 123

Cloudera

APRIL 27, 2022

The financial services industry has had to dedicate more resources to personalisation, fighting fraud, and reducing cloud concentration risk. Real-time access to accurate data on customers that drives machine learning models are crucial to the accuracy of predictions or recommendations they make in real time.

IoT 99

IoT IT Manufacturing Internet of Things 99

Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal.

Data Science 110

Data Science Statistics Predictive Analytics Recreation/Entertainment 110

IBM Big Data Hub

MAY 18, 2023

This report outlines the combination of traditional decision automation tools with machine learning models and other technologies. As Forrester notes in the report, many organizations are eager to harness the power of AI but also must be cautious of risks.

Reporting 87

Reporting Scorecard Predictive Modeling Machine Learning 87

Smarten

MAY 31, 2022

The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ It is meant to identify crucial relationships and opportunities and risks and help the organization to accurately predict: Growth.

Predictive Analytics 69

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 69

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

Smarten

AUGUST 6, 2024

So, if a power user or business users discovers a challenge or an opportunity and your management team wishes to further explore the issue to understand its strategic or operational value, a Data Scientist can take the predictive model or other analytical report produced by a Citizen Data Scientist and refine the results for executive review.

Predictive Modeling 64

Predictive Modeling Key Performance Indicator Data-driven Finance 64

Cloudera

MAY 12, 2021

We welcome organizations that have built and deployed use cases for enterprise-scale machine learning and have industrialized AI to automate, secure, and optimize data-driven decision-making and/or applications to enter this category. PEOPLE FIRST. A new award category for 2021. Read more about last years Data Impact Award winners.

Digital Transformation 70

Digital Transformation Machine Learning Optimization Data Lake 70