Finance professionals often stick to proven methods, understanding that disrupting established systems can jeopardize time-sensitive financial processes. However, with the blinding pace of technological change, it becomes nearly impossible to keep up even with the advantages of advanced ERP systems like SAP ECC and S/4 HANA. For organizations entrenched in legacy SAP systems, stalled financial transformation can be a major roadblock to success.

Apache Flink offers a variety of APIs that provide users with significant flexibility in processing data streams. Among these, the Table API stands out as one of the most popular options. Its user-friendly design allows developers to express complex data processing logic in a clear and declarative manner, making it particularly appealing for those who want to efficiently manipulate data without getting bogged down in intricate implementation details.

Welcome to the September edition of “What’s New in Loadero”! Along with various fixes we also have an announcement to make about something that is external to the app’s functionality - our blog!

The evolution of APIs (application programming interfaces) has been all the hype in recent years. In many ways, they're powering the modern internet as they open doors to organizations and developers around the globe. Data shows that 98% of enterprise leaders believe APIs are essential for survival concerning digital transformation, yet most struggle to develop a comprehensive rollout strategy.

Enterprises have complex IT and technology needs. To reach business goals, organizations must often stitch together a patchwork of software and IT systems. So, it’s understandable that the thought of adding yet another technology—low-code—might cause trepidation. But low-code excels at integrating seamlessly with any technology. Low-code tools speed up development work and enable rapid application development.

Picture this: You are part of a BI team at a global garment manufacturer with dozens of factories, warehouses, and stores worldwide. Your team is tasked with extracting insights from company data. You begin the ETL (Extract, Transform, Load) process but find yourself struggling with the manual effort of understanding table structures and revisiting and modifying pipelines due to ongoing changes in data sources or business requirements.

Science fiction no longer defines Artificial Intelligence (AI) as a futuristic trend. It now forms an essential part of our everyday life, quietly but significantly impacting how society and businesses run. AI is changing businesses and paving the way for a new era of innovation and expansion. It does this by automating routine tasks and guiding complex decision-making processes.

A relatively new term in the world of data management, data mesh refers to the process of creating a single, unified view of all enterprise data. This process can happen in several ways, giving business users easy access to the data they require for decision-making. Several principles guide data mesh design and implementation. This article will discuss the principles of data mesh and how they can help your business get the most out of its data.

For many Microsoft Dynamics NAV users, migrating to Dynamics 365 Business Central (BC) is a daunting prospect. It’s often perceived as a time-consuming and expensive process that disrupts day-to-day operations. However, delaying the migration is no longer an option. Microsoft discontinued development of NAV in 2018, and mainstream support ended in 2023. Extended support is limited, and without a timely upgrade, you risk losing functionality and performance.

We sometimes have customers tell us they want to run end-to-end tests as often as possible in their development processes — as often as every commit. When you really care about quality, this might seem like a reasonable idea. After all, doesn’t the principle of shift left tell us to test as early as possible in the software development lifecycle? To catch bugs and other issues when they’re the least-expensive to fix?