IBM Big Data Hub

MAY 1, 2023

The early versions of AI were capable of predictive modelling (e.g., The four categories of predictive modelling, robotics, speech and image recognition are collectively known as algorithm-based AI or Discriminative AI. It offers customers and the insurer’s system to interact in a human-like manner.

Insurance 79

Insurance Predictive Modeling Cost-Benefit Statistics 79

CIO Business Intelligence

OCTOBER 5, 2023

CBRE has also used AI to optimize portfolios for several clients, and recently launched a self-service generative AI product that enables employees to interact with CBRE and external data in a conversational manner. For AI, the high-value quadrant is where you’ll find most predictive modeling.

Experimentation 129

Experimentation Strategy Machine Learning Interactive 129

DataRobot

MARCH 2, 2021

Every day, millions of people interact with AI systems, often without knowing it. 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.

Predictive Modeling 98

Predictive Modeling Risk Consulting Dashboards 98

Smarten

JUNE 8, 2022

Predictive analytics uses data integrated from appropriate data sources, and augmented analytics allows the business to anticipate production demands, plan for new locations and markets and predict targeted customer buying behavior and changes in product demand across multiple market segments. Analyzing Customer Churn.

Predictive Analytics 52

Predictive Analytics Predictive Modeling Forecasting Optimization 52

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

Business Over Broadway

SEPTEMBER 27, 2018

Figure 1 includes a good illustration of different data sets and how they fall along these two size-related dimensions (For the interested reader, check out the figure in an interactive graphic ). 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

FineReport

APRIL 9, 2024

The implementation of robust healthcare data management strategies is imperative to mitigate the risks associated with data breaches and non-compliance. The integration of clinical data analysis tools empowers healthcare providers to leverage predictive analytics for proactive decision-making.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

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. Computer Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Birst BI

OCTOBER 30, 2018

A personal crystal ball that predicts your days ahead is what financial services firms everywhere want. Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? Will this next trade return a profit?

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Smarten

JANUARY 31, 2019

Today’s Advanced Analytics Tools allow business users to leverage features like self-serve data preparation, smart data visualization and assisted predictive modeling.

Business Intelligence 40

Business Intelligence Analytics Predictive Modeling Forecasting 40

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. Budget constraints for cybersecurity and perception that their organization is sufficiently protected.

Cost-Benefit 58

Cost-Benefit Machine Learning Consulting Data mining 58

Smarten

APRIL 2, 2019

Smart Data Visualization allows users to view and analyze data to identify a problem and clarify a root cause and to interact easily with data discovery tools and analytics software to build a view that will tell a story using guided visualization and recommended data presentation so there is no need for assistance or delays.

Analytics 40

Analytics Predictive Modeling Visualization Cost-Benefit 40

Cloudera

JULY 18, 2018

We recently announced the availability of MetiStream Ember on top of Cloudera, which offers an end-to-end interactive analytics platform specifically for the healthcare and life sciences industries. 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

DataRobot Blog

NOVEMBER 9, 2017

I’ve spent the last 2+ years working with business analysts and MBA’s to build predictive models. You could: Change the way your company handles sales prospects by ranking them with a machine learning model. Enhance the way people interact with your product by adding voice assistance. You’ve got to start somewhere.

Machine Learning 52

Machine Learning Data-driven Software Sales 52

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 169

Testing Data Quality Predictive Modeling Metrics 169

O'Reilly on Data

SEPTEMBER 19, 2023

” Each step has been a twist on “what if we could write code to interact with a tamper-resistant ledger in real-time?” 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.”

Machine Learning 247

Machine Learning Testing Modeling Cost-Benefit 247

CIO Business Intelligence

AUGUST 15, 2023

A risk-limiting audit (RLA) is one audit type used for election verification. The scalable avatar can have hundreds of thousands of conversations individually and simultaneously, and is highly customizable and interactive in real-time, thereby providing an immersive experience for each user.

IT 98

IT Manufacturing IoT Cost-Benefit 98

O'Reilly on Data

SEPTEMBER 15, 2020

This in turn would increase the platform’s value for users and thus increase engagement, which would result in more eyes to see and interact with ads, which would mean better ROI on ad spend for customers, which would then achieve the goal of increased revenue and customer retention (for business stakeholders).

Cost-Benefit 293

Cost-Benefit Advertising ROI Machine Learning 293

CIO Business Intelligence

JUNE 22, 2022

Despite this, only a handful of organisations interact with all stages of the data life cycle process to truly distill information that distinguishes future-ready businesses from the rest. The financial services industry has had to dedicate more resources to personalisation, fighting fraud, and reducing cloud concentration risk.

IoT 96

IoT IT Manufacturing Internet of Things 96

Cloudera

APRIL 27, 2022

Despite this, only a handful of organisations interact with all stages of the data life cycle process to truly distill information that distinguishes future-ready businesses from the rest. The financial services industry has had to dedicate more resources to personalisation, fighting fraud, and reducing cloud concentration risk.

IoT 94

IoT IT Manufacturing Internet of Things 94

Domino Data Lab

JANUARY 21, 2021

Predictive modeling efforts rely on dataset profiles , whether consisting of summary statistics or descriptive charts. Results become the basis for understanding the solution space (or, ‘the realm of the possible’) for a given modeling task. There is a risk of injecting bias. imputation of missing values).

Statistics 106

Statistics Unstructured Data Data Science Visualization 106

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

IBM Big Data Hub

DECEMBER 20, 2023

For instance, if data scientists were building a model for tornado forecasting, the input variables might include date, location, temperature, wind flow patterns and more, and the output would be the actual tornado activity recorded for those days. Manage a range of machine learning models with watstonx.ai temperature, salary).

Machine Learning 77

Machine Learning Modeling Deep Learning Predictive Modeling 77

FineReport

APRIL 24, 2024

Interactivity: Incorporating interactive features allows users to explore the data more deeply, gaining comprehensive insights from the visualizations. Moreover, interactive features in data visualization tools allow users to delve deeper into the data, exploring specific data points or segments with ease.

Visualization 52

Visualization Dashboards Interactive Key Performance Indicator 52

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 118

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 118

DataRobot Blog

JANUARY 10, 2023

Clinics and hospitals like Phoenix Children’s use AI to predict which patients are at risk of contracting an illness so that they can then prescribe medication and treatment accordingly. Built-in Code Snippets and Interactive Visualizations to Accelerate Experimentation.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

Insight

MARCH 18, 2019

Bias in Machine Learning Algorithms (Bottom Photos Source: ProPublica ; Top Photos Source: Pexels.com) Biases in predictive modeling are a widespread issue Machine learning and AI applications are used across industries, from recommendation engines to self-driving cars and more. Overview of what this project aims to build.

Machine Learning 77

Machine Learning Predictive Modeling Modeling Metrics 77

Alation

APRIL 14, 2022

Supports the ability to interact with the actual data and perform analysis on it. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. Parametrization. A technique to automate changes in iterative passes. Pattern Matching. Visual Profiling. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

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 Diagnostic Analytics 157

Domino Data Lab

JULY 9, 2019

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Domino Data Lab

AUGUST 1, 2021

The need for interaction – complex decision making systems often rely on Human–Autonomy Teaming (HAT), where the outcome is produced by joint efforts of one or more humans and one or more autonomous agents. This dataset classifies customers based on a set of attributes into two credit risk groups – good or bad.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. Predictive analytics indicates what might happen in the future with an acceptable level of reliability, including a few alternative scenarios and risk assessment. Data exploded and became big.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

JUNE 25, 2018

Business Problem: A stock broker wants to analyze the price volatility of a stock as a measure of risk. Business Benefit: By analyzing the standard deviation or variance, one can measure the risk associated with a particular stock in terms of price fluctuations. 5) Standard Deviation/Variance. 6) Skewness/Histogram. About Smarten.

Statistics 40

Statistics Enterprise Measurement Business Intelligence 40

Depict Data Studio

SEPTEMBER 17, 2019

David focuses especially on helping researchers embrace the power of the internet to communicate with online, interactive reporting. Combining skills in research, data visualization, website design, and digital reporting, David Keyes is a consultant who helps researchers creatively communicate their work.

Visualization 40

Visualization Consulting Dashboards Reporting 40

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

O'Reilly on Data

MARCH 24, 2020

John Myles White , data scientist and engineering manager at Facebook, wrote: “The biggest risk I see with data science projects is that analyzing data per se is generally a bad thing. We’ve seen a lot of headway made in democratizing and automating data collection and building models.

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346

Jet Global

SEPTEMBER 1, 2023

But we’re also seeing its use expand in other industries, like Financial Services applications for credit risk assessment or Human Resources applications to identify employee trends. Using the information from predictive analytics can help companies—and business applications—suggest actions that can affect positive operational changes.

Predictive Analytics 52

Predictive Analytics Risk Analytics Software 52