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Creating a data warehouse with custom order processing systems
技术
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 设备与机械
适用功能
- 离散制造
- 商业运营
用例
- 供应链可见性(SCV)
- 库存管理
服务
- 系统集成
- 数据科学服务
挑战
Fabick Cat, a tractor dealer specializing in the distribution of Caterpillar® equipment, faced a challenge when it acquired a second Caterpillar dealership. The newly acquired dealership had its own custom-written order processing system running on OpenVMS with RMS files, different from Fabick Cat's IBM® AS/400 based system. Fabick Cat wanted a solution to provide a data warehouse for both systems to ensure uniform reporting and analytics for both companies. The initial plan was to FTP files from the OpenVMS server and load them into SQL Server. However, the amount of data downloaded every day and the manual nature of this approach raised concerns.
关于客户
Fabick Cat is a tractor dealer that specializes in the distribution of Caterpillar® equipment. The company’s product line consists of more than 300 machines, including articulated trucks, backhoe loaders, compactors, front shovels, hydraulic excavators, motor graders, paving equipment, and off-highway trucks. It also offers a wide range of rentals. The company was established in 1917 and maintains a facility in Fenton, Miss., U.S. Today, there are more than 1,100 employees including members of the Fabick family’s third, fourth, and fifth generations, working together under the active leadership of the founder’s great-grandson, Douglas Fabick, as CEO and Dealer Principal along with Jeré Fabick serving as President and co-Dealer Principal.
解决方案
Fabick Cat decided to use CONNX DataSync, a micro-batch, low-latency Change Data Capture (CDC) solution that keeps data fresh and up-to-date without impacting the performance of data sources. DataSync enables companies to maintain data warehouses with minimal effort or system requirements, delivering near real-time data integration and continuous refreshes by incrementally updating only those records that have changed. With the database synchronization software, companies can schedule updates to optimize system performance based on individual needs. Depending on the demand, updates can be scheduled for lower-use periods, such as after normal business hours, or as frequently as every minute when more up-to-date data is needed.
运营影响
数量效益
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