Systems | Development | Analytics | API | Testing

Welcome to the latest entry in Yellowfin Japan’s ‘How to?’ blog series! This series of blogs aims to provide your team with another hands-on example of adding data visualization to your Yellowfin dashboards, using our array of chart and graph types. In the previous blog, we created a Combination Chart by aggregating on the basis of Year and Month.

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.

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.

The last decade has seen a giant shift by organizations into the cloud for software, storage, and compute, resulting in business benefits ranging from flexibility and lower up-front costs to easier maintenance. But lately we have seen more and more companies re-evaluating their cloud strategies and opting to move their data back to on-premises infrastructure due to several key factors.

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.

MIT research shows data governance is the precursor to effective AI implementation.

Imagine having all your critical business metrics and project data seamlessly integrated within your favorite project management tool. For ClickUp users, this vision becomes a reality with the embedding of Databox dashboards. No more toggling between multiple platforms or juggling tools — embedding a Databox dashboard into ClickUp centralizes your insights, empowering you to make informed decisions without missing a beat.

The year is 1424. You’re shipping goods across the world, and the ship in question gives you a bill of lading. It’s a piece of paper containing details about what your goods are, where you’re shipping them from, and where they’re headed. Fast forward to 2024. You’re shipping your goods across the world, and the shipping company gives you a bill of lading. It’s still (most likely) a piece of paper.

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.