article thumbnail

PCI compliance: The best defense is a great defense

CIO Business Intelligence

PCI DSS compliance is a robust defense that significantly mitigates the risks involved with all three. Researchers for the 2023 DBIR identified system intrusion, social engineering and basic web application attacks as the most common attack patterns that led to breaches and data theft.

article thumbnail

How to unlock a scientific approach to change management with powerful data insights

IBM Big Data Hub

Process mining tools can perform a fit-gap analysis on new processes to rapidly and more accurately identify the greatest change impacts. This goes hand in hand with our appreciation that ‘change is always changing’ and we need to keep pace or risk falling behind.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

SEC climate-related disclosure rules for public companies

IBM Big Data Hub

However, there will be a phase-in period for compliance, with the largest companies reporting, as required, on climate-related risks by fiscal year 2025 and on emissions by 2026. IBM offers products that help organizations track and report their environmental impact, and their exposure to climate risk. How can IBM help?

Risk 57
article thumbnail

How healthcare organizations can analyze and create insights using price transparency data

AWS Big Data

This is due to the complexity of the JSON structure, contracts, and the risk evaluation process on the payor side. As hospitals generate this data, they can use their organization data or ingest data from other hospitals to derive analytics and competitive comparison.

article thumbnail

The art and science of data product portfolio management

AWS Big Data

At the same time, unstructured approaches to data mesh management that don’t have a vision for what types of products should exist and how to ensure they are developed are at high risk of creating the same effect through simple neglect. How do we define “risk” and “value” in the context of data products, and how can we measure this?