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The appropriate way to structure a search request for optimizing a dataset would depend on the specific requirements and goals of the optimization process. However, the following general steps can be taken:

1. Define the goal: Clearly define the goal of the optimization process, such as improving data quality, reducing data storage space, or enhancing data processing speed.

2. Identify the dataset: Identify the dataset that needs to be optimized, including its size, format, and structure.

3. Evaluate the current state: Evaluate the current state of the dataset, including any issues or shortcomings that need to be addressed.

4. Analyze the data: Analyze the data to identify any patterns, trends, or anomalies that could be causing problems in the dataset.

5. Identify optimization techniques: Identify the optimization techniques that could be used to improve the dataset, such as normalization, data deduplication, indexing, or data compression.

6. Prioritize optimization techniques: Prioritize the optimization techniques based on their impact on the dataset and the resources required for implementation.

7. Create a plan: Create a plan for implementing the optimization techniques, including timelines, resource allocations, and risk mitigation strategies.

8. Execute the plan: Execute the plan and monitor the results of the optimization process to ensure that the goals are being achieved.

9. Iterate: Iterate the optimization process as needed to continue improving the dataset over time.