Successful AI relies on a number of factors including a large corpus of data, the requisite algorithms, expert data scientists with appropriate skills, and appropriate compute resources. The latter means not just physical and virtual server infrastructure, but also data management and database software designed to support high-performance data processing and analytics.
Data management is a critical enabler of machine learning projects because it helps overcome challenges such as accessing and preparing data, which can be a significant barrier to success. The results of 451 Research’s Voice of the Enterprise: AI & Machine Learning survey, conducted with people directly involved in AI and ML initiatives, illustrates the point: 33% of respondents cited accessing and preparing data as a barrier the use of machine learning, and 15% cited it as the most significant barrier.