Data integration involves combining data from several disparate sources, which are stored using various technologies and provide a unified view of the data. Data integration becomes increasingly important in cases of merging systems of two companies or consolidating applications within one company to provide a unified view of the company's data assets. Probably the most well known implementation of data integration is building an enterprise's data warehouse. The benefit of a data warehouse enables a business to perform analyses based on the data in the data warehouse. This would not be possible to do on the data available only in the source system. The reason is that the source systems may not contain corresponding data, even though the data are identically named, they may refer to different entities.
Several distinct sub-areas are:
Enterprise application/information integration
Master data management
Bigger challenge lies in the entirety of data integration:
Why is the data integration being done?
What are the objectives and deliverables?
From what systems will the data be sourced?
Is all the data available to fulfill the requirements?
What are the business rules?
What is the support model and SLA?
What is the support model for the new system? What are the SLA requirements?
A feasibility study should be performed to select the tools to implement the data integration system. Small companies and enterprises which are starting with data warehousing are faced with making a decision about the set of tools they will need to implement the solution.
Both technical IT and business needs to participate in the testing to ensure that the results are as expected/required. Therefore, the testing should incorporate at least Performance Stress test (PST), Technical Acceptance Testing (TAT) and User Acceptance Testing (UAT ) PST, TAT (Technical Acceptance Testing), UAT (User Acceptance Testing).
Data Integration Techniques: There are several organizational levels on which the integration can be performed.
Manual Integration or Common User Interface
Application Based Integration
Middleware Data Integration
Uniform Data Access or Virtual Integration
Common Data Storage or Physical Data Integration
You need an API integration platform so you can meet the need of best-of-breed solutions:
Many departments—including 96 percent of account and finance teams—are building their own solutions, assembling their own platforms, by pulling together best-of-breed solutions that handle specific tasks and datasets. With a Salesforce API integration platform, departments are able to easily connect the best apps and tools. If you’re considering large-scale adoption of Salesforce-based applications (or the Lightning Platform or Database.com tool sets) so that you can become familiar with the integration capabilities and options available. Architects and developers should consider these pattern details and best practices during the design and implementation phase of a Salesforce integration project. These patterns enable you to get to production as fast as possible and have the most stable, scalable, and maintenance-free set of applications possible.
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