FineReport

APRIL 9, 2024

The integration of clinical data analysis tools empowers healthcare providers to leverage predictive analytics for proactive decision-making. Through the utilization of predictive models, clinicians can forecast patient outcomes and resource needs, enabling early intervention and personalized care delivery.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

Birst BI

OCTOBER 30, 2018

The output of these algorithms, when used in financial services, can be anything from a customer behavior score to a prediction of future trading trends, to flagging a fraudulent insurance claim. The credit scores generated by the predictive model are then used to approve or deny credit cards or loans to customers.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Smarten

JUNE 26, 2018

Finance – An organization might use this technique to Identify if demographic factors influence banking channel/product/service preference or selection of a type of term plan of an insurance etc. How Can the Chi Square Test of Association Be Used for Business Analysis?

Testing 40

Testing Statistics IT Business Intelligence 40

AWS Big Data

MARCH 7, 2023

It enables you to create interactive dashboards, visualizations, and advanced analytics with ML insights. It helps you build, train, and deploy models consuming the data from repositories in the data hub. Decoupled and scalable – Serverless, auto scaled, and fully managed services are preferred over manually managed services.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

CIO Business Intelligence

AUGUST 15, 2023

Shamim Mohammad, CIO, CarMax CarMax That volume created a Sisyphean task for the company’s content writers, as they struggled to provide up-to-date information by make, model, and year for each vehicle in the company’s constantly changing inventory.

IT 98

IT Manufacturing IoT Cost-Benefit 98

DataRobot Blog

MAY 25, 2022

DataRobot enables the user to easily combine multiple datasets into a single training dataset for AI modeling. DataRobot combines these datasets and data types into one training dataset used to build models for predicting whether a building will be damaged in the hurricane. Quickly and Easily Build Models. The Datasets.

Risk 52

Risk Predictive Modeling Insurance Predictive Analytics 52

Smarten

JULY 10, 2018

Use Case(s): Determine if a product sells better in certain locations, verify if gender has an influence on purchasing decisions, Identify if demographic factors influence banking channel/product/service preference or selection of a type of term insurance plan and more.

Analytics 40

Analytics Forecasting Statistics Sales 40

Domino Data Lab

AUGUST 20, 2019

Feature engineering is useful for data scientists when assessing tradeoff decisions regarding the impact of their ML models. It is a framework for approaching ML as well as providing techniques for extracting features from raw data that can be used within the models. We can also modify the features before we start the modeling process.

Testing 68

Testing Modeling Interactive Measurement 68

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade. See Ribeiro et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Smarten

JUNE 21, 2018

This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment. Time series forecasting methods are used to extract and analyze data and statistics and characterize results to more accurately predict the future based on historical data.

Forecasting 40

Forecasting Enterprise IT Predictive Modeling 40