Believe it or not, there was a time when healthcare providers, global enterprises, Ecommerce stores, and other organizations used proprietary—and often very different—methods to communicate with other businesses for everything from invoices to purchase orders. You can maybe imagine how difficult communication between businesses was before the introduction of EDI.

As a seasoned content moderator with a keen eye for detail and a passion for upholding the highest standards of quality and integrity in all of their work, Spencer Nguyen brings a professional yet empathetic approach to every task.

‍ The rise of artificial intelligence (AI) in testing is enabling more predictive and intelligent test generation, execution, and defect analysis. This shift aims to reduce the time and effort required for manual testing to enhance test coverage and improve the overall software quality. Justifiably, key insights from Fortune Business project the growth of the AI-enabled testing market from USD 736.8 million in 2023 to USD 2,746.6 million by 2030.

Every business has key customer behaviors it aims to drive — whether it's encouraging repeat purchases, promoting product upgrades or boosting add-on services. Yet, despite access to advanced marketing technology and rich customer profiles, most businesses still rely on broad, generalized lifecycle marketing campaigns that fail to engage with customers.

The benefits of API mocking extend beyond just speeding up development. It enables developers to work independently of external APIs, eliminating delays caused by dependencies that may be out of their control. This independence is crucial for maintaining workflow efficiency, especially in complex projects involving multiple APIs. API mocking is invaluable for testing edge cases and error scenarios that might be difficult to reproduce with a live API.

A database is a critical piece of software for any organization. It stores data and allows users to access and modify it as needed. Many different databases are available, like AWS' Amazon RDS or Microsoft's Azure, so deciding which is suitable for your organization can be challenging. This article will discuss the different kinds of databases and help you choose the right database for your needs.

It’s nearing the end of the summer in North America, and one report has been a staple on my reading list for more than a decade: the Flexera State of the Cloud Report. The annual survey of hundreds of global IT decision makers assesses cloud strategies, migration trends, and important considerations for companies moving to the cloud or managing cloud environments.

Over the years, Amazon DynamoDB has grown into a feature-rich NoSQL database that has deep integrations with various services such as Amazon S3 and AWS Lambda. As businesses increasingly depend on data for decision-making, it is common to use data residing in DynamoDB to contextualize or even drive events at a granular level (as opposed to bulk or batch).

Across industries worldwide, businesses are turning to ERP to automate repetitive tasks, enjoy easy scalability, stay flexible, and derive insights using a single source of truth. According to Statista, Enterprise Resource Planning (ERP) software market revenue will reach USD 53.15 billion this year. If your organization implements an ERP system, you’ll find that data migration is one of the most critical components of this process.

Not too long ago, businesses tended to downplay the importance of integrating analytics into their operational strategies and embracing digital big data. The formidable challenges of hefty budgets and a need for more qualified digital transformation professionals were major barriers, deterring companies from fully engaging with the big data era.