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 73

Risk Modeling Management Metadata 73

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

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

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

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 Technology 52

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 Risk Cost-Benefit Technology 138

IBM Big Data Hub

MARCH 7, 2023

The challenge was gleaning relevant insights from the vast amount of data collected to help identify those infants at risk. The specific approach we took required the use of both AI and edge computing to create a predictive model that could process years of anonymized data to help doctors make informed decisions.

Risk 52

Risk Technology Informatics Predictive Modeling 52

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 50

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 50

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 90

IT Machine Learning Risk Optimization 90

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

Cloudera

JUNE 27, 2023

Adopting an MDA is more efficient and cost effective than legacy data architectures which are siloed, poorly governed, with vast redundant data sets and data processes that are expensive and expose the company to risk. Modernize data flows. Most telcos rely on legacy applications that create data silos and limit interoperability.

Data Architecture 62

Data Architecture Predictive Modeling Data Governance Data-driven 62

FineReport

APRIL 9, 2024

From advanced analytics to predictive modeling, the evolving landscape of business intelligence is revolutionizing how data is processed and leveraged for actionable insights. Proactive Risk Management : BI tools enable organizations to proactively identify potential risks through predictive modeling and trend analysis.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

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 91

Reporting Scorecard Predictive Modeling Machine Learning 91

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 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

Risk 359

Risk Modeling Data Processing Software 359

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 129

Experimentation Strategy Machine Learning Interactive 129

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

IBM Big Data Hub

AUGUST 14, 2023

Under-deployed tools and solutions that do the minimal that’s “good enough” or that face other barriers like the risk aversion to fully automating processes that could have unintended consequences. UBA’s Machine Learning Analytics add-on extends the capabilities of QRadar by adding use cases for ML analytics.

Cost-Benefit 58

Cost-Benefit Machine Learning Consulting Data mining 58

IBM Big Data Hub

MAY 17, 2024

But as businesses around the globe rapidly adopt the technology to augment processes from merchandising to order management, there is some risk. By using machine learning algorithms and big data analytics, AI can uncover patterns, correlations and trends that might escape human analysts.

B2B 67

B2B Interactive Optimization Forecasting 67

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 65

Digital Transformation Machine Learning Optimization Data Lake 65

IBM Big Data Hub

JUNE 29, 2023

Sensors collect data in real-time that is then fed into an enterprise asset management (EAM) or computerized maintenance management system (CMMS), where AI-enhanced data analysis tools and processes like machine learning (ML) spot issues and help resolve them.

Cost-Benefit 84

Cost-Benefit Measurement Management Predictive Analytics 84

Smarten

JUNE 25, 2019

Augmented analytics allows for data prep, Smart Data Visualization and Assisted Predictive Modeling with the help of machine learning and natural language processing (NLP), so users need not be trained as data scientists to get to the heart of the data and find those elusive nuggets of information that will help them create, change and improve.

Analytics 51

Analytics Predictive Modeling Visualization Machine Learning 51

DataRobot

JUNE 4, 2021

DataRobot enables organizations to leverage the transformational power of machine learning by delivering the world’s most trusted enterprise AI platform that spans the full lifecycle from data to value. Here, we have a model that predicts foot traffic for a chain of coffee shops. Forecasting In-Store Foot Traffic.

Forecasting 52

Forecasting Machine Learning Predictive Modeling Modeling 52

IBM Big Data Hub

FEBRUARY 14, 2024

Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. Automotive With applications of AI, automotive manufacturers are able to more effectively predict and adjust production to respond to changes in supply and demand.

Cost-Benefit 85

Cost-Benefit Insurance Unstructured Data Machine Learning 85

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 Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

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 77

Machine Learning Modeling Deep Learning Predictive Modeling 77

Smarten

AUGUST 21, 2019

Assisted Predictive Modeling – These tools enable the average business user to leverage sophisticated predictive algorithms without requiring statistical or data science skills. Users can highlight trends and patterns, test hypotheses and theories to reduce business risk, and easily predict and forecast results.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

DataRobot Blog

APRIL 1, 2022

Steward uses machine learning to make big decisions about staff and patients, reduce costs, and improve patient outcomes and experiences, and they have already started achieving their goal of decreasing costs. Also, degrading models over time can pose a significant risk to the business. Challenge #3.

Machine Learning 59

Machine Learning Cost-Benefit Predictive Modeling Modeling 59

DataRobot Blog

AUGUST 10, 2022

NHS organisations are used to using workforce KPIs to manage staffing levels, but the real opportunity is being able to identify staff that are at risk of leaving post and to implement strategies to retain their much needed talent. Resetting urgent care performance and delivery. Improving patient outcomes through a data-first approach.

Forecasting 52

Forecasting Experimentation Data-driven Risk 52

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 Cost-Benefit Data mining 83

IBM Big Data Hub

MAY 6, 2024

Enter the age of data-driven protocol assessment: using benchmarking tools and predictive modeling to gauge protocol intricacies and forecast eligible patient numbers, which then inform protocol adjustments. Ensuring early assumptions resonate with real-world execution is paramount.

Advertising 69

Advertising Data-driven Optimization Strategy 69

DataRobot Blog

JUNE 23, 2022

Your artificial intelligence (AI) system has given you this “predicted feature” in addition to what you already know about the applicant. Business rules set by the credit committee to control business risk and the loan portfolio also constrain accepting this application and advancing the loan. What Decisions Can Change – and How?

Predictive Modeling 59

Predictive Modeling Modeling Data Science Measurement 59

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

DataRobot Blog

NOVEMBER 9, 2017

I work for a software company that has built an automated machine learning platform. I’ve spent the last 2+ years working with business analysts and MBA’s to build predictive models. We started offering a course called Data Science, Machine Learning, and AI for Executives a while back, and it’s been very successful.

Machine Learning 52

Machine Learning Data-driven Software Sales 52

O'Reilly on Data

JANUARY 17, 2023

Building Models. A common task for a data scientist is to build a predictive model. You know the drill: pull some data, carve it up into features, feed it into one of scikit-learn’s various algorithms. You might say that the outcome of this exercise is a performant predictive model.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

Smarten

DECEMBER 3, 2023

Augmented analytics can help the business to improve revenue and to discover product and service opportunities and gain insight into issues to resolve problems before they create risk. Unscrambl highlights a few of the ways major businesses have used analytics to help improve competitive positioning and to solve problems.

Analytics 40

Analytics Cost-Benefit Data Quality Consulting 40