CSRHub Big Data Series

“Big Data” is a useful tool for rating corporate social responsibility (CSR) and sustainability performance. We believe that the Big Data system that CSRHub has developed is one answer to dealing with the rise in new ratings systems (it seems there is a new one announced each month) and with the disparities in scores that occur among these different systems. This is a three part series.

Content from this campaign

AI & Technology
CSRHub Celebrates Reaching 900 ESG Data Sources
CSRHub has now ingested more than 900 sources of ESG data. Our database consists of 600 million pieces of ESG data on more than 50,000 entities.
Environment
Why Use Big Data to Measure CSR?
In the past several posts, we have defined Big Data, shown the problems we hope it will address, and described how CSRHub has implemented a Big Data approach to creating corporate social responsibility (CSR) and sustainability ratings. It is time now to discuss the benefits and drawbacks of the “Big Data” approach.
Environment
A Big Data Approach to Gathering CSR Data
CSRHub uses input from investor-driven sources (known as “ESG” for Environment, Social, and Governance or “SRI” for Socially Responsible Investment), non-governmental organizations, government organizations, and “crowd sources” to construct a 360 degree view of a company’s sustainability performance.
Environment
Using “Big Data” to Rate Corporate Social Responsibility: One Company’s Approach
“Big Data” is a useful tool for rating corporate social responsibility (CSR) and sustainability performance. We believe that the Big Data system that CSRHub has developed is one answer to dealing with the rise in new ratings systems (it seems there is a new one announced each month) and with the disparities in scores that occur among these different systems.