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

Sisense

MARCH 27, 2019

Unlike traditional models that look at historical data for patterns, real-time analytics focuses on understanding information as it arrives to help make faster, better decisions. To provide real-time data, these platforms use smart data storage solutions such as Redshift data warehouses , visualizations, and ad hoc analytics tools.

Business Intelligence 74

Business Intelligence Data Warehouse Predictive Modeling Visualization 74

Cloudera

JANUARY 5, 2023

This is especially so in industries like telecom, retail, healthcare, manufacturing, insurance, and financial services. What will determine the winners from the laggards will hinge on the speed at which predictive analytics can be executed, and the cost-benefit ratio related to these algorithmic paradigms.

Cost-Benefit 52

Cost-Benefit Business Objectives Machine Learning Data Architecture 52

Birst BI

JANUARY 16, 2018

For the vast majority of information workers, this is the definition of self-service analytics. But to build that dashboard, someone has to assemble all the components, the key performance indicators (KPIs), the data visualizations, and all of the dashboard’s data feeds. The barrier of entry to BI remains high.

Data-driven 70

Data-driven Analytics Dashboards Machine Learning 70

Domino Data Lab

JULY 28, 2021

In its current form , data science is limitless in terms of industry and application; the only requirement is data, compute power, data scientists, and a desire to become model-driven. These advances have had huge ramifications across industries ranging from finance and banking to healthcare and insurance. The Data Science Toolkit.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

datapine

OCTOBER 21, 2020

Now that we live longer, treatment models have changed and many of these changes are namely driven by data. By utilizing key performance indicators in healthcare and healthcare data analytics, prevention is better than cure, and managing to draw a comprehensive picture of a patient will let insurance provide a tailored package.

Big Data 364

Big Data Data Analytics Analytics Cost-Benefit 364

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

Domino Data Lab

JULY 22, 2019

how “the business executives who are seeing the value of data science and being model-informed, they are the ones who are doubling down on their bets now, and they’re investing a lot more money.” He also really informed a lot of the early thinking about data visualization. Predictive analytics, yeah, not so much.”

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Decision Management Solutions

FEBRUARY 25, 2019

To keep processing costs low, many insurance carriers have a goal to increase the percentage of their claims that can be processed and decisioned with no human decision-making involved. Perhaps surprisingly, there remains a fair amount of human intervention involved in processing insurance claims. Design and build a decision model.

Insurance 40

Insurance Management Machine Learning Modeling 40

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

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise. IBM watsonx.ai

Machine Learning 67

Machine Learning Data Warehouse Modeling Cost-Benefit 67

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process.

Data Analytics 90

Data Analytics Analytics Data Warehouse Data Lake 90

Domino Data Lab

JUNE 2, 2019

We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively. Data science leadership: importance of being model-driven and model-informed.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

Smarten

JULY 10, 2018

This article summarizes our recent article series on the definition, meaning and use of the various algorithms and analytical methods and techniques used in predictive analytics for business users, and in augmented data preparation and augmented data discovery tools.

Analytics 40

Analytics Forecasting Statistics Sales 40

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

Andrew White

JANUARY 11, 2021

As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. Try some gamification?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52