Remove Data Collection Remove Data Integration Remove Risk Management
article thumbnail

Managing risk in machine learning

O'Reilly on Data

At the recent Strata Data conference we had a series of talks on relevant cultural, organizational, and engineering topics. Here's a list of a few clusters of relevant sessions from the recent conference: Data Integration and Data Pipelines. Data Platforms. Model lifecycle management.

article thumbnail

CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it

CIO Business Intelligence

However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive. Developers, data architects and data engineers can initiate change at the grassroots level from integrating sustainability metrics into data models to ensuring ESG data integrity and fostering collaboration with sustainability teams.

IT 59
Insiders

Sign Up for our Newsletter

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

article thumbnail

What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

article thumbnail

The 10 most in-demand IT jobs in finance

CIO Business Intelligence

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98
article thumbnail

The 10 most in-demand IT jobs in finance

CIO Business Intelligence

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98
article thumbnail

Your Effective Roadmap To Implement A Successful Business Intelligence Strategy

datapine

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Because it is that important. Think of security, privacy, and compliance.

article thumbnail

AI’s Achilles heel: Securing the next revolution

CIO Business Intelligence

Regulatory frameworks like the EU AI Act and NIST AI Risk Management Framework are shaping expectations around responsible AI deployment. Balancing security, ethics and strategic investments Securing AI systems requires a balanced approach that integrates technical rigor with strategic foresight: Invest in AI-specific security.

Risk 116