Find a dataset of 1 million records with 10 features (refer to online sources like Kaggle, UCI machine learning repo, etc. ), where each feature is a categorical variable. The task is to identify the top 10 features that have the highest correlation with the target variable. Implement a solution using a combination of Python pandas and the sci-kit-learn library. The solution should be able to handle the large scale of the data and use dimensionality reduction techniques such as PCA or Lasso to reduce the number of features and select the most relevant features.

a. Above described dataset link

b. Python code with the above-described functionality