Dataconomy

DECEMBER 25, 2024

The global predictive analytics market in healthcare, valued at $11.7 Healthcare providers now use predictive models to forecast disease outbreaks, reduce hospital readmissions, and optimize treatment plans. Major data sources for predictive analytics include EHRs, insurance claims, medical imaging, and health surveys.

Analytics 91

Analytics Analytics Predictive Analytics Machine Learning 91

Data Science Blog

JULY 23, 2023

Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. Process Mining offers process transparency, compliance insights, and process optimization.

Data Science 246

Data Science Azure Power BI Business Intelligence 246

Data Science Blog

NOVEMBER 15, 2023

Storing the Object-Centrc Analytical Data Model on Data Mesh Architecture Central data models, particularly when used in a Data Mesh in the Enterprise Cloud, are highly beneficial for Process Mining, Business Intelligence, Data Science, and AI Training.

Data Modeling 245

Data Modeling Data Models Business Intelligence Business Intelligence 245

Pickl AI

OCTOBER 15, 2024

Diagnostic Analytics Diagnostic analytics goes a step further by explaining why certain events occurred. It uses data mining , correlations, and statistical analyses to investigate the causes behind past outcomes. It analyses patterns to predict trends, customer behaviours, and potential outcomes.

Analytics 52

Analytics Analytics Predictive Analytics Machine Learning 52

Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Big Data Analytics 52

Pickl AI

JANUARY 19, 2025

Summary: Data warehousing and data mining are crucial for effective data management. Data warehousing focuses on storing and organizing data for easy access, while data mining extracts valuable insights from that data. It ensures data quality, consistency, and accessibility over time.

Data Mining 52

Data Mining Data Mining Data Mining Data Warehouse 52