What is the correct order of the steps of the Identity Resolution process?

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Multiple Choice

What is the correct order of the steps of the Identity Resolution process?

Explanation:
This question tests the sequence used to build and verify Identity Resolution. It starts with profiling data across data sources to understand what fields exist, how reliable they are, and where quality issues or gaps lie. Knowing the data landscape upfront helps you choose meaningful identifiers and anticipate normalization needs. After profiling, you configure match rules. With a clear view of the data, you specify how records from different sources should be compared—which fields to use, what matching thresholds, and whether to apply exact or fuzzy matching. This step defines how potential duplicates or the same entity across sources are identified. Next you set up reconciliation rules. Once matches are determined, you decide how to merge information, resolve conflicts, and determine which source wins or how to combine attributes. This ensures consistent, canonical records once matches are found. Finally, you validate results. You test the outcomes, assess match quality with metrics like precision and recall, review duplicates, and adjust rules as needed before deploying. This order matters because profiling informs effective matching rules, and only after matches are established can you apply thoughtful reconciliation. Validation then confirms the system meets business requirements. Other sequences skip or jumble these dependencies, leading to poor matches or unresolved ambiguities.

This question tests the sequence used to build and verify Identity Resolution. It starts with profiling data across data sources to understand what fields exist, how reliable they are, and where quality issues or gaps lie. Knowing the data landscape upfront helps you choose meaningful identifiers and anticipate normalization needs.

After profiling, you configure match rules. With a clear view of the data, you specify how records from different sources should be compared—which fields to use, what matching thresholds, and whether to apply exact or fuzzy matching. This step defines how potential duplicates or the same entity across sources are identified.

Next you set up reconciliation rules. Once matches are determined, you decide how to merge information, resolve conflicts, and determine which source wins or how to combine attributes. This ensures consistent, canonical records once matches are found.

Finally, you validate results. You test the outcomes, assess match quality with metrics like precision and recall, review duplicates, and adjust rules as needed before deploying.

This order matters because profiling informs effective matching rules, and only after matches are established can you apply thoughtful reconciliation. Validation then confirms the system meets business requirements. Other sequences skip or jumble these dependencies, leading to poor matches or unresolved ambiguities.

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