APIs for Data Consistency Across Disparate Systems Saves Time and Money for Beverage Distribution Company
Beverage distribution is complex. Surprisingly, it’s also data heavy. So much so that one of the largest beverage distribution companies in the United States struggled with multiple databases across their business.
With variable growth in 11 different regions, the company was faced with integrating 11 database instances, each with their own Customer database schema, stored in a legacy system, with a Master Data Management (MDM) system as their new source of truth. Because customer data was used across departments, from sales to warehouse and distribution, it was crucial that data be updated across systems and in near real-time. Data transformation was also required.
Big Compass was invited to partner on the development of the solution for this beverage distributor. To meet the organization’s requirements, a solution that included MuleSoft, Azure queues, and Salesforce was architected.
In order to capture and propagate Customer updates, System APIs were created. One for the database instances to listen for updates, another for the company’s SaaS MDM solution, and a third that listened for events from Salesforce.
Given that each end system represents the Customer in a different way, a process layer was created. The process layer transforms data into a common Customer data model, simplifying the interaction between the databases, the MDM, and Salesforce. The process layer also coordinates batch loading and event queuing for the data synchronization solution.
MuleSoft was a critical piece of the puzzle, helping the architects and developers interact with the wide variety of systems in the solution, including IBM AS400, Salesforce, and the SaaS MDM platform. The solution is also designed for future components such as Snowflake.
The implementation is still in progress, but the client already realizes a reduction in errors, better data quality, consistency, and a standardized synchronization timeline thanks to the iterative development process. When completed, the distributor will have a robust Customer Master Data Management (MDM) solution, which provides both immediate benefits and sets the stage for continued improvement and modernization.
ADOPTION & EXPANSION
+ Number of APIs
+ Business coverage
+ Number of contracted apps
+ API usage
+ API reuse
EFFICIENCY & COST SAVINGS
+ Number of APIs in each SDLC stage
+ Time spent in each SDLC stage
+ Cost and time to build an API
+ App development velocity
+ Number of launches per year
+ Number of defects
SECURITY & VULNERABILITIES
Time since the last version was published
Number of throttling issues
+ Time to onboard
+ Number of deployments
+ Number of incidents
+ Percentage of customers impacted. per incident
+ Time to resolve incidents