Building A High-performance Data And AI Organization - AI Summary

Along with poor data quality, these issues combine to deprive organizations' data platforms--and the machine learning and analytics models they support--of the speed and scale needed to deliver the desired business results. To understand how data management and the technologies it relies on are evolving amid such challenges, MIT Technology Review Insights surveyed 351 CDOs, chief analytics officers, chief information officers (CIOs), chief technology officers (CTOs), and other senior technology leaders. They are succeeding thanks to their attention to the foundations of sound data management and architecture, which enable them to "democratize" data and derive value from machine learning. Pushing these to the edge with advanced data technologies will help end-users to make more informed business decisions -- the hallmarks of a strong data culture. Organizations' top data priorities over the next two years fall into three areas, all supported by wider adoption of cloud platforms: improving data management, enhancing data analytics and ML, and expanding the use of all types of enterprise data, including streaming and unstructured data.