input: 
  from typing import Tuple, List
  
  def create_data_visualization_dashboard(x_data: List[float], y_data: List[float], 
                                          figsize: Tuple[int, int] = (10, 6), 
                                          color: str = 'green', marker: str = 'o', 
                                          linestyle: str = 'dashed', linewidth: int = 2, 
                                          markersize: int = 12, title: str = "My Data Visualization Dashboard", 
                                          xlabel: str = 'X-axis', ylabel: str = 'Y-axis') -> None:
      """ Create a data visualization dashboard using Python and Matplotlib.
      This function will generate a line plot based on the input x and y data, 
      and configure the plot attributes as specified.
      >>> create_data_visualization_dashboard([1, 2, 3, 4, 5], [10, 25, 30, 50, 80])
      # Will display the dashboard with default settings
      >>> create_data_visualization_dashboard([1, 2, 3, 4, 5], [10, 25, 30, 50, 80], 
                                              figsize=(8, 4), color='blue', marker='s', 
                                              linestyle='-', title="Sales Data", xlabel="Months", ylabel="Sales")
      # Will display the customized dashboard with specified settings
      """
      
      import matplotlib.pyplot as plt
      
      # Create the figure and set the size
      fig = plt.figure(figsize=figsize)
      
      # Configure the plot
      plt.plot(x_data, y_data, color=color, marker=marker, linestyle=linestyle, linewidth=linewidth, markersize=markersize)
      plt.title(title)
      plt.xlabel(xlabel)
      plt.ylabel(ylabel)
      
      # Show the plot
      plt.show()
  
output:     import matplotlib.pyplot as plt
      
      # Create the figure and set the size
      fig = plt.figure(figsize=figsize)
      
      # Configure the plot
      plt.plot(x_data, y_data, color=color, marker=marker, linestyle=linestyle, linewidth=linewidth, markersize=markersize)
      plt.title(title)
      plt.xlabel(xlabel)
      plt.ylabel(ylabel)
      
      # Show the plot
      plt.show()