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This chapter is from the book

This chapter is from the book

Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable ArchitectureData Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture

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This chapter is from the book

This chapter is from the book

Data Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable ArchitectureData Integration Blueprint and Modeling: Techniques for a Scalable and Sustainable Architecture

Learn More Buy

Summary

Data modeling is a graphical design technique for data. In data integration, data integration modeling is a technique for designing data integration processes using a graphical process modeling technique against the data integration reference architecture.

This chapter detailed the types of data integration models—conceptual, logical, and physical—and the approach for subdividing the models based on the process layers of the data integration reference architecture. This chapter also provided examples of each of the different logical and physical data integration model types.

It covered the transition from logical data integration models to physical data integration models, which might be better stated as how to move from the "whats" to the "hows."

Finally, the chapter discussed how this maturing technique can be used to create prebuilt, industry-based data integration models.

The next chapter is a case study for a bank that is building a set of data integration processes and uses data integration modeling to design the planned data integration jobs.

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