DataRobot Blog

JULY 22, 2022

Using AI-based models increases your organization’s revenue, improves operational efficiency, and enhances client relationships. You need to know where your deployed models are, what they do, the data they use, the results they produce, and who relies upon their results. That requires a good model governance framework.

Modeling 105

Modeling Risk Management Testing Risk 105

O'Reilly on Data

SEPTEMBER 19, 2023

Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.” And it was good.

Machine Learning 335

Machine Learning Testing Modeling Cost-Benefit 335

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. from 2022 to 2028.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

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

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

SEPTEMBER 10, 2024

We envisioned harnessing this data through predictive models to gain valuable insights into various aspects of the industry. This included predicting political outcomes, such as potential votes on pipeline extensions, as well as operational issues like predicting the failure of downhole submersible pumps, which can be costly to repair.

IT 122

IT Risk Risk Management Predictive Modeling 122

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. The fourth pillar focuses on testing the results of data models, visualizations, and other applications to validate data in use.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Smart Data Collective

MARCH 3, 2021

When the risk of recurrence for a malpractice case is high, for example, they can convince the judge to be more generous in rewarding the client. The impact of predictive modelling on personal injury cases. Predictive modelling is a technology that evolved together with big data analytics.

Analytics 133

Analytics Big Data Predictive Modeling Insurance 133

Smart Data Collective

SEPTEMBER 17, 2020

Here are a few of the advantages of Big Data in the banking and financial industry: Improvement in risk management operations. Big Data can efficiently enhance the ways firms utilize predictive models in the risk management discipline. Big Data provides financial and banking organizations with better risk coverage.

Big Data 145

Big Data Finance Risk Management Risk 145

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

Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. Hollywood is a $10 billion-a-year industry, and movies range from huge hits to box office bombs.

Risk 67

Risk ROI Modeling Metrics 67

Smart Data Collective

MARCH 23, 2022

This AI could be utilized as a safety feature , like real-time risk assessment, for example, alerting the driver when a potential incident has been detected. Utilizing advanced heuristics and AI modeling OEMs can simulate a multitude of conditions, fast-tracking these models using automation.

Internet of Things 131

Internet of Things IoT Cost-Benefit Testing 131

DataRobot Blog

MAY 25, 2022

The DataRobot AI Cloud Platform can also help identify infrastructure and buildings at risk of damage from natural disasters. DataRobot enables the user to easily combine multiple datasets into a single training dataset for AI modeling. Quickly and Easily Build Models. In 2017, Hurricane Harvey struck the U.S. The Datasets.

Risk 52

Risk Predictive Modeling Insurance Predictive Analytics 52

CIO Business Intelligence

MARCH 19, 2025

Developers, data architects and data engineers can initiate change at the grassroots level from integrating sustainability metrics into data models to ensuring ESG data integrity and fostering collaboration with sustainability teams. Highlight how ESG metrics can enhance risk management, regulatory compliance and brand reputation.

IT 59

IT Data Governance Data-driven Metrics 59

CIO Business Intelligence

MAY 14, 2024

Enterprises need to ensure that private corporate data does not find itself inside a public AI model,” McCarthy says. You don’t want a mistake to happen and have it end up ingested or part of someone else’s model. Such private cloud solutions eliminate the risks of multitenancy data leakage, for example, a key CIO concern with AI.

IT 143

IT Data Processing Enterprise Modeling 143

CIO Business Intelligence

DECEMBER 11, 2023

Traditionally, the work of the CFO and the finance team was focused on protecting the company’s assets and reputation and guarding against risk. They can even optimize capital allocation decisions, such as dividend distribution versus share buy-back, by rapidly modeling multiple scenarios and market conditions.

Finance 105

Finance Forecasting IoT Predictive Modeling 105

IBM Big Data Hub

JANUARY 25, 2024

Yet many AI creators are currently facing backlash for the biases, inaccuracies and problematic data practices being exposed in their models. The math demonstrates a powerful truth All predictive models, including AI, are more accurate when they incorporate diverse human intelligence and experience.

Predictive Modeling 83

Predictive Modeling Modeling Risk Statistics 83

Business Over Broadway

SEPTEMBER 27, 2018

pharmacogenomics) and risk assessment of genetic disorders (e.g., In this scenario, marketing analytics can only be conducted within one data silo at a time, decreasing your model’s predictive power / increasing your model’s error. Machine Learning and Predictive Modeling of Customer Churn.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

DataRobot Blog

JUNE 3, 2022

The influence of the GPT-3 language model has the potential to be both beneficial and misused. . Generative Pre-trained Transformer 3 (GPT-3) is a language model that utilizes deep-structured learning to predict human-like text. Similarly, no one is focused on smaller models. What is GPT-3? When is enough ever enough?

Risk 52

Risk Predictive Modeling Modeling Machine Learning 52

DataRobot

OCTOBER 19, 2021

DataRobot helped combat this problem head on by applying AI to evaluate and predict resource allocation and identify the most impacted communities from a national to county level. On average, DataRobot forecasts had a 21 percent lower rate of error than all other published competing models over a six to eight week period. White Paper.

Forecasting 98

Forecasting Predictive Modeling Optimization Testing 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. Usage in a business context. The end-user is another factor to consider.

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

DataRobot

MARCH 2, 2021

With DataRobot, you can build dozens of predictive models with the push of a button and easily deploy them. Monitoring deployed models is easy because we provide features to check on service health, data drift, and accuracy. We can help with data preparation and AI development, deployment, and monitoring.

Predictive Modeling 98

Predictive Modeling Risk Dashboards Consulting 98

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

CIO Business Intelligence

JUNE 22, 2022

Predictive maintenance applications enable large-scale manufacturers to collect telemetry data and integrate all IoT functions, and these are powered by models driven by real-time data. . The financial services industry has had to dedicate more resources to personalisation, fighting fraud, and reducing cloud concentration risk.

IoT 98

IoT IT Manufacturing Internet of Things 98

BizAcuity

NOVEMBER 13, 2024

Making decisions based on data, rather than intuition alone, brings benefits such as increased accuracy, reduced risks, and deeper customer insights. Advanced Analytics and Predictive Insights The real value of data lies in its ability to forecast trends and identify opportunities.

Consulting 52

Consulting Data-driven Cost-Benefit Business Intelligence 52

Cloudera

APRIL 27, 2022

Predictive maintenance applications enable large-scale manufacturers to collect telemetry data and integrate all IoT functions, and these are powered by models driven by real-time data. . The financial services industry has had to dedicate more resources to personalisation, fighting fraud, and reducing cloud concentration risk.

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. A simple example is the case of missing values.

Data Science 110

Data Science Statistics Predictive Analytics Recreation/Entertainment 110

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. Nor can we learn prediction intervals across a large set of parallel time series, since we are trying to generate intervals for a single global time series.

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

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

Smart Data Collective

MAY 23, 2021

While this can be classed as data science, one difference is that data science tends to use a predictive model to make its analysis, while AI can be capable of analyzing based on learned knowledge and facts. One way that AI can be used to benefit your tech company is to carry out risk analysis. The benefits to your tech company.

Data Science 118

Data Science Cost-Benefit Statistics Predictive Modeling 118

Occam's Razor

AUGUST 9, 2021

Forward-looking allocations are based on simulations that can take all of the above, to answer low, medium, high-risk plans – from which our senior leader gets to choose the one she believes aligns with her strategic vision. My hypothesis is that you are not spending a lot of time on predictive metrics and predictive modeling.

Metrics 143

Metrics Analytics Key Performance Indicator Predictive Modeling 143

Smarten

MAY 13, 2019

While one may think of fraud most commonly associated with financial and banking organizations or IT functions or networks, industries like healthcare, government and public sector are also at risk. Businesses that are proactive in identifying these risks can better optimize resources and respond to changing trends and patterns.

Predictive Analytics 11

Predictive Analytics Analytics Predictive Modeling Risk 11

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

CIO Business Intelligence

AUGUST 23, 2023

That need for complex mathematical modeling at scale makes the finance industry a perfect candidate for the promise of quantum computing, which makes (extremely) quick work of computations, including complex ones, delivering results in minutes or hours instead of weeks and months.

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. In the training phase, the primary objective is to use existing examples to train a model.

Machine Learning 105

Machine Learning Cost-Benefit Modeling Risk 105

Smarten

MARCH 12, 2020

A solution that provides a balance between data agility and access and data governance and security can provide solid, dependable information and the ability for users to leverage Self-Serve Data Preparation , Assisted Predictive Modeling and Smart Data Visualization while protecting the organization from risk and mitigating security issues.

Data Governance 69

Data Governance Predictive Modeling Data-driven Visualization 69

CIO Business Intelligence

OCTOBER 5, 2023

“We’ve seen so many initiatives fail when it’s technology for technology’s sake,” says Davé, who suggests two means of avoiding this mistake: prioritization models aligned to your business strategy and strategic partnerships. Let’s start with the models. For AI, the high-value quadrant is where you’ll find most predictive modeling.

Experimentation 130

Experimentation Strategy Machine Learning Interactive 130