To build a successful business, you need to find innovative ways to reach out to existing customers and bring on new ones. How? Through cross-selling efforts, more targeted marketing campaigns, and greater attention to customer service. But when critical customer data resides on multiple source applications such as CRM, ERP, financial applications and Web servers – especially as the result of a merger or acquisition – gaining a single and consistent view of the customer isn’t always easy.
CDI is a combination of technologies and processes that consolidate data from across the organization to create a centralized view of the customer. CDI solutions are used to deliver the most complete, real-time views of people, households and organizations from data dispersed across multiple application systems and databases.
CDI technology frameworks are based on a service-oriented architecture (SOA) to provide enterprise-wide infrastructure for managing and harmonizing master “customer data” such as: customers, products, suppliers, and employees.
Customer Data Integration (CDI) solutions bring it all together by maintaining a single view of critical customer data and synchronizing the data across all other mission-critical applications. Critical customer data flows in real-time between multiple applications for a single view of the customer – who they are, what they’ve bought and plan to buy, how they interact, and much more. With consistent customer data, you make better business decisions, exchange data and interact with customers, and react immediately to recognize and meet their unique needs.
CDI has become an important initiative within organizations that prioritize a consolidated view of customer information across the organization. CDI enables organizations to build a centralized customer data store and to manage that process. Specialized considerations should be taken into account when implementing a CDI solution versus an overall data integration initiative. Key components to identify and match with vendor functionality are data cleansing and standardization, data profiling and data mapping. These factors, when combined, allow data quality to increase and to be managed over time.
MDM is to provide and maintain a consistent view of an organization’s core business entities, which may involve data that is scattered across a range of application systems.
The type of data involved in this process varies by industry and organization, but examples: include customers, suppliers, products, employees and finances. Presently, many MDM applications concentrate on the handling of customer data because this aids the sales and marketing process, and can help improve sales and thus revenues.
Master Data Management (MDM), also known as Reference Data Management, is a discipline in Information Technology (IT) that focuses on the management of reference or master data that is shared by several disparate IT systems and groups. MDM is required to warrant consistent computing between diverse system architectures and business functions.
MDM applications that are focused on the inbound data (aggregation) and the outbound master record (distribution) in turn use data integration applications and data integration technologies. Data integration applications solve data integration problems using one or more data integration techniques (data consolidation, data federation, data propagation, changed data capture, data transformation). These techniques are implemented using one of more data integration technologies (EII, ETL, EAI, EDR, ECM, etc.).