A fictitious large European car manufacturer (let's call it "FiGEA" for short) sells and services its vehicles through a network of many dealers in the Far East. Each dealer operates its own IT systems, which vary in size and complexity depending on the dealership size. Each of them manages its own customer data, sales and services in its own language and according to local laws. In addition, due to acquisitions and IT legacy development, FiGEA has multiple, partially inconsistent IT systems for different business functions and/or regions.
How can FiGEA become an integrated digital company that consolidates data from all dealers and internal departments to optimize its operations, define and track KPIs locally and internationally, and provide excellent sales and service to all its customers bangladesh telegram screening and partners? How can FiGEA hope to achieve even a small part of this goal if it does not have a complete, unified master list of its customers?
Attempts to clean and consolidate the customer master record using data wrangling tools fail early on. Each merchant's data must be imported and cleaned individually, but this approach cannot apply to customers who buy from multiple merchants. In addition, such manual systems are extremely difficult to apply to constantly changing data that must support real-time operational and reporting systems.
As an ICMS, CortexDB enables the creation of an integrated set of all customer data that is distillable - cleaned and reconciled - continuously and automatically. Each distinct customer record from any system, both internal and external, is stored individually, time-stamped and in its raw format in the CortexDB document store. There is no need to define a consistent structure, naming or order of data fields in advance. New or changed schemas can be handled just as easily. Each record, with full historical sequencing, consists of an unordered and unconstrained set of key/value pairs stored forever. Storing a complete set of customer records in their original form as raw data is a prerequisite for ongoing distillation and required auditing.