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There are several ways to personalize data profiles in Azure ML Studio:

1. Selecting the columns to profile - you can choose which columns to include in your data profile by selecting them from the dataset.

2. Choosing the type of data profile - Azure ML Studio provides several different types of data profiles, including basic statistics, histogram, box plot, scatter plot, and correlation matrix. You can choose the type of profile that best suits your needs.

3. Setting profiling options - you can configure the data profiling options, such as choosing the number of bins for the histogram or selecting the correlation method for the correlation matrix.

4. Using custom scripts - if the built-in data profiling options do not provide the information you need, you can create custom scripts to profile the data.

5. Using external tools - Azure ML Studio allows you to use external tools, such as R or Python, to perform data profiling and analysis.