AI Articles and Analysis about Data analysis

Analysis of data, also known as data analytics, is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.

Short Term and Long Term ROI for AI in Finance@2x-min

Short Term and Long Term ROI for AI in Finance – with Matthias Steinberg of MindBridge

This interview analysis is sponsored by MindBridge and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Bringing Trust and Guardrails into Developing Enterprise AI Systems@2x

Bringing Trust and Guardrails into Developing Enterprise AI Systems – with Steve Jones of Capgemini

This interview analysis is sponsored by Capgemini and was written, edited, and published in alignment with our Emerj-sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Artificial Intelligence at Blue Cross Blue Shield-2x

Artificial Intelligence at Blue Cross Blue Shield

Blue Cross Blue Shield (BCBS) is a federation of 35 independent health insurance companies that provide coverage to over 100 million Americans. The organization's national headquarters is located in Chicago, Illinois, while individual BCBS companies operate in various states across the country.

The Future of Insurance Workflows with AI@2x

The Future of Insurance Workflows with AI – with George Williams of Nationwide and Heather Wilson of CLARA Analytics

This interview analysis is sponsored by CLARA Analytics and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Driven Approaches 
to Infrastructure

Driving Patient Experiences Through Data Science-Driven Approaches to Infrastructure – with Xiong Liu of Novartis

Explainable AI models are essential in pharmaceutical R&D because they provide transparency and understanding of how AI-driven predictions are made. In drug discovery and development, stakeholders, including researchers, regulatory bodies, and healthcare professionals, need to trust and understand AI models' outputs to make informed decisions. Without explainability, AI models can be seen as "black boxes," leading to skepticism and reluctance to adopt these technologies in critical decision-making processes. 

V.1 – How AI Drives Drug Development Workflows and Value Chains Across Life Sciences Enterprises-1x-min

How AI Drives Drug Development Workflows and Value Chains Across Life Sciences Enterprises – with Leaders from Benevolent and Takeda

This article/interview analysis is sponsored by BenevolentAI and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Artificial Intelligence at Elevance Health-1-min

Artificial Intelligence at Elevance Health

Elevance Health is a health insurance provider headquartered in Indianapolis, Indiana. It was founded 20 years ago as a merger between Anthem and Wellpoint Health Networks. The company offers medical, dental, pharmaceutical, behavioral health, and long-term care plans.

IT for Financial Services in the Age of GenAI-min

IT for Financial Services in the Age of GenAI – with Craig Mackereth of Rimini Street

Dozens of GPT-driven products are already on the market, and hundreds more are in development. These tools collectively aim to revolutionize traditional roles and processes, transforming them into dynamic, parallelized workflows using variants of LLM models, such as AutoGPT. Tools like GitHub Copilot, powered by OpenAI's Codex, are demonstrating significant improvements in developer productivity, with some studies showing up to a 55% increase in task completion speed. 

Data analysis

Analysis of data, also known as data analytics, is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.