Amongst the oldest and most well-known ERP solutions, JD Edwards and PeopleSoft have together delivered decades of tangible business value to their customers and continue to release innovative new features and functionality that help organizations modernize their operations. As cloud solutions become more ubiquitous and more enterprise businesses consider cloud investments, many options are now available to JD Edwards and PeopleSoft customers.

Some companies choose to run their existing JD Edwards or PeopleSoft solutions in the cloud on platforms like Azure, AWS or Oracle Cloud Infrastructure. Others start their cloud journey by moving select functions (often previously supported by 3rd party applications) to Oracle Cloud applications. Still others contemplate a full ‘lift and shift’ strategy, replacing their on-prem solutions with one or more Oracle Cloud applications.

For organizations who have not yet made the move to cloud, the benefits of migration are clear: lower cost of total ownership, increased operational agility, greater automation and modernization of existing business functions, but determining the optimal path to the cloud is not always easy.

Quest Oracle Community supports thousands of JD Edwards and PeopleSoft users world-wide, creating opportunities for customers to share insights, innovations and best practices through its education programs, networking activities and special interest groups. In a recent benchmarking survey, Quest invited its members to share where they are on their cloud journeys, which (if any) Oracle Cloud applications they are actively using or considering as well as challenges they have encountered as they develop and implement their cloud strategies.

There has been no shortage of attention on the advantages artificial intelligence and generative AI bring to enterprises - from real-time customer engagement to on-the-spot analysis and remediation of issues or anomalies. Behind all the wonders that AI brings, however, is the workhorse that must be attended behind the scenes—databases and associated data environments. Data managers acknowledge that in many cases, today’s current data environments inhibit progress, and improvement requires more targeted investment in automation and infrastructure. Data needs to be secure, highly available, and viable for AI and other advanced initiatives to succeed within enterprises.