Our new eBook “Data-Driven Analytics Use Cases Powered by the Actian Cloud Data Platform” is designed for users and application builders looking to address a wide range of data analytics, integration, and edge use cases. We have included the following examples from real-world customer experiences and deployments to serve as a guide to help…
In today's highly competitive business world, companies are constantly looking for ways to improve their supply chain operations. One of the most effective ways to do this is by measuring supply chain performance using real-time analytics. By understanding the performance of each aspect of the supply chain, companies can identify bottlenecks, reduce lead times,…
Supply chain analytics uses data and advanced analytics to analyze and optimize various aspects of the supply chain, including procurement, manufacturing, and logistics. The main goals of supply chain analytics are to improve efficiency, lower costs, and increase revenue. Supply chain analytics can also provide real-time insights that help businesses adjust to changing conditions…
When a company is data-driven, it makes strategic decisions based on data analysis and interpretation rather than mere intuition. A data-driven approach to supply chain management is the key to building a strong supply chain, one that’s efficient, resilient, and that can easily adapt to changing business conditions. How exactly you can best incorporate…
When it comes to supply chain data, there’s an intriguing story to be told. If businesses have access to accurate data in real time about their supply chain operations, they have tremendous opportunities to increase efficiency, reduce costs, and grow revenue. Here’s a look at some of the types of supply chain data and…
Supply chains have undergone—and continue to experience—major changes and disruption. Worker shortages, rapidly changing customer demands, logistics problems, transportation bottlenecks, and other factors have all contributed to challenges. Even sales patterns that used to be easy to predict, such as those based on holidays and seasonal buying, have become much harder to understand, amplifying…
Processing data in real-time Every organization processes data in many ways. For example, batch data process still exists for heavy data-process workloads, such as payroll. Many of these data processing requirements are executed by batch scheduling software; however, there is a growing need for data processing to be more automated and processed in real-time.…
