You could do this with python and a couple of libraries. This is just an example, but you could import the data from a DB or use a CSV file.

import matplotlib.pyplot as plt
import numpy as np

# Pie chart data
labels = ['Category A', 'Category B', 'Category C', 'Category D', 'Category E']
sizes = [30, 25, 20, 15, 10]
colors = ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']

# Pie chart
plt.figure(figsize=(8, 8))
plt.pie(sizes, labels=labels, colors=colors, autopct='%1.1f%%', startangle=140)
plt.title('Sample Pie Chart')
plt.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle.
plt.show()

# Histogram data
data = np.random.normal(0, 1, 1000) # Generate 1000 random data points with a normal distribution

# Histogram
plt.figure(figsize=(10, 6))
plt.hist(data, bins=30, color='#66b3ff', edgecolor='black')
plt.title('Sample Histogram')
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.show()