How Data Engineering Enhances the Business Value In Today's World
Big Data Issues Limit Analytics While businesses are quickly embracing data-centric efforts, many are having trouble with the procedures and technology needed to put models into use. According to a Gartner poll, the most difficult problem for data and analytics leaders is integrating their work into current business processes and platforms. Not coding but data management at scale presents AI and advanced analytics with their greatest difficulty. Writing ML code is only a small component of what makes projects successful. The effectiveness of a project's data models will determine whether it is an AI success. Organizations will need to figure out how to integrate their data initiatives across business units and processes as data sources continue to vary over time. In order to effortlessly move from data testing to the production process, they must also concentrate on making the appropriate data accessible. And it is in this area where the newly popular technique of data engineering...