In some cases, if not all too some extent, integration between Dynamics™ CRM, Salesforce® or/and SharePoint® with your back-office system is the key to user adoption. Real-time, two-way data integration allows all segments of the business to access the very latest transactional data, and the information that the data contains. One example might be the keying of a ‘large’ order by a sales representative into CRM or Salesforce. Having real-time, two-way data integration in place, that order would go directly from the crm system to your ERP/MRP system for processing. That in turn will reduce inventory and alert the operations team, signaling the purchasing department that orders need to be placed to backfill inventory and, signaling the operation manager that they will need to increase production to fulfill the ‘large’ order. In some cases the integration of data can trigger an alert that will notify outside vendors directly that inventory needs to be replenished.
With access to current inventory levels within a sales rep’s CRM or Salesforce system, sales reps can make better informed customer promises with regard to when items will ship and/or if ordered items will be backordered. This greatly improves customer satisfaction and adoption of the new CRM or Salesforce system. Other advantages (among a plethora) is integration into SharePoint as well, where lists can be compiled to help make better business decision as well as having vital documents at your fingertips, which ever application you are currently using.
This is just one small example of how application data integration can improve adoption, and also improve the client’s business prospects. My purpose in this blog is not to discuss the business benefits of data integration, but explore some of the architectural hurdles in designing the real-time, two-way data integration processes. In a short series of blog entries, we’ll examine:
How data is discovered for translation
When to discover data for translation
What data to discover for translation
How to handle concurrent data modification
How to incorporate the client’s and the application’s
business rules into the integration processes
We will, by no means, cover all the detail that goes into data integration, but will cover, at a high level, some of the hurdles and how to overcome them. In some cases, there will be a choice of methods to accomplish a task, so, we’ll also talk about the best method to use in particular situations. Some methods are tool agnostic, some will highlight how a tool like Scribe Insight provides easy access to data and the business rules around the data. We’ll also see that many of the methods are application agnostic, meaning they can be applied to any system to system integration.
Data integration can be tricky stuff if it’s your first time tackling the subject. Whether you are implementing a solution, or just need to talk comfortably about integration, there are several things to be careful of, but having said that, like anything else, it’s just a matter of experience before your comfort level is one that keeps your knees from shaking and your palms from sweating.
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