diff --git a/data/santander_bank.db b/data/santander_bank.db
new file mode 100644
index 00000000..6248bdd4
Binary files /dev/null and b/data/santander_bank.db differ
diff --git a/scripts/load_data.py b/scripts/load_data.py
new file mode 100644
index 00000000..e4bc01e3
--- /dev/null
+++ b/scripts/load_data.py
@@ -0,0 +1,254 @@
+"""Script to create SQLite database and load Excel data.
+
+This script creates the santander_bank.db database with customers and
+transactions tables, then loads data from the corresponding Excel files.
+"""
+
+# Standard library
+import sqlite3
+from pathlib import Path
+
+# Third-party
+import pandas as pd
+
+
+def create_database(db_path: str) -> sqlite3.Connection:
+    """Create a new SQLite database connection.
+
+    Args:
+        db_path: Path where the database file should be created.
+
+    Returns:
+        SQLite connection object.
+    """
+    conn = sqlite3.connect(db_path)
+    print(f"Created database: {db_path}")
+    return conn
+
+
+def create_customers_table(conn: sqlite3.Connection) -> None:
+    """Create the customers table with appropriate schema.
+
+    Args:
+        conn: SQLite database connection.
+    """
+    cursor = conn.cursor()
+    cursor.execute("""
+        CREATE TABLE IF NOT EXISTS customers (
+            customer_id TEXT PRIMARY KEY,
+            first_name TEXT NOT NULL,
+            last_name TEXT NOT NULL,
+            email TEXT,
+            phone TEXT,
+            date_of_birth TEXT,
+            age INTEGER,
+            gender TEXT,
+            address TEXT,
+            city TEXT,
+            postcode TEXT,
+            account_type TEXT,
+            account_number INTEGER,
+            sort_code TEXT,
+            account_open_date TEXT,
+            balance REAL,
+            income_bracket TEXT,
+            credit_score INTEGER,
+            num_products INTEGER,
+            customer_segment TEXT,
+            is_active INTEGER,
+            has_mobile_app INTEGER,
+            has_online_banking INTEGER,
+            marketing_consent INTEGER
+        )
+    """)
+    conn.commit()
+    print("Created customers table")
+
+
+def create_transactions_table(conn: sqlite3.Connection) -> None:
+    """Create the transactions table with appropriate schema.
+
+    Args:
+        conn: SQLite database connection.
+    """
+    cursor = conn.cursor()
+    cursor.execute("""
+        CREATE TABLE IF NOT EXISTS transactions (
+            transaction_id TEXT PRIMARY KEY,
+            customer_id TEXT NOT NULL,
+            transaction_date TEXT,
+            transaction_time TEXT,
+            transaction_type TEXT,
+            category TEXT,
+            amount REAL,
+            currency TEXT,
+            merchant_name TEXT,
+            merchant_category_code INTEGER,
+            channel TEXT,
+            location TEXT,
+            is_international INTEGER,
+            is_recurring INTEGER,
+            status TEXT,
+            FOREIGN KEY (customer_id) REFERENCES customers(customer_id)
+        )
+    """)
+    conn.commit()
+    print("Created transactions table")
+
+
+def load_customers_data(conn: sqlite3.Connection, excel_path: str) -> int:
+    """Load customer data from Excel file into the database.
+
+    Args:
+        conn: SQLite database connection.
+        excel_path: Path to the customers Excel file.
+
+    Returns:
+        Number of rows loaded.
+
+    Raises:
+        FileNotFoundError: If the Excel file doesn't exist.
+    """
+    if not Path(excel_path).exists():
+        raise FileNotFoundError(f"Excel file not found: {excel_path}")
+
+    df = pd.read_excel(excel_path)
+
+    bool_columns = ["is_active", "has_mobile_app", "has_online_banking", "marketing_consent"]
+    for col in bool_columns:
+        if col in df.columns:
+            df[col] = df[col].astype(int)
+
+    df.to_sql("customers", conn, if_exists="replace", index=False)
+    print(f"Loaded {len(df)} rows into customers table")
+    return len(df)
+
+
+def load_transactions_data(conn: sqlite3.Connection, excel_path: str) -> int:
+    """Load transaction data from Excel file into the database.
+
+    Args:
+        conn: SQLite database connection.
+        excel_path: Path to the transactions Excel file.
+
+    Returns:
+        Number of rows loaded.
+
+    Raises:
+        FileNotFoundError: If the Excel file doesn't exist.
+    """
+    if not Path(excel_path).exists():
+        raise FileNotFoundError(f"Excel file not found: {excel_path}")
+
+    df = pd.read_excel(excel_path)
+
+    bool_columns = ["is_international", "is_recurring"]
+    for col in bool_columns:
+        if col in df.columns:
+            df[col] = df[col].astype(int)
+
+    df.to_sql("transactions", conn, if_exists="replace", index=False)
+    print(f"Loaded {len(df)} rows into transactions table")
+    return len(df)
+
+
+def verify_data(conn: sqlite3.Connection) -> None:
+    """Run sample queries to verify data was loaded correctly.
+
+    Args:
+        conn: SQLite database connection.
+    """
+    cursor = conn.cursor()
+
+    print("\n" + "=" * 60)
+    print("DATA VERIFICATION")
+    print("=" * 60)
+
+    cursor.execute("SELECT COUNT(*) FROM customers")
+    customer_count = cursor.fetchone()[0]
+    print(f"\nTotal customers: {customer_count}")
+
+    cursor.execute("SELECT COUNT(*) FROM transactions")
+    transaction_count = cursor.fetchone()[0]
+    print(f"Total transactions: {transaction_count}")
+
+    print("\n--- Sample Customers (first 5) ---")
+    cursor.execute("""
+        SELECT 
+            customer_id,
+            first_name,
+            last_name,
+            city,
+            account_type,
+            balance
+        FROM customers
+        LIMIT 5
+    """)
+    for row in cursor.fetchall():
+        print(f"  {row}")
+
+    print("\n--- Sample Transactions (first 5) ---")
+    cursor.execute("""
+        SELECT 
+            transaction_id,
+            customer_id,
+            transaction_date,
+            transaction_type,
+            amount,
+            status
+        FROM transactions
+        LIMIT 5
+    """)
+    for row in cursor.fetchall():
+        print(f"  {row}")
+
+    print("\n--- Customer Transactions Summary ---")
+    cursor.execute("""
+        SELECT 
+            c.customer_id,
+            c.first_name || ' ' || c.last_name AS customer_name,
+            c.city,
+            COUNT(t.transaction_id) AS transaction_count,
+            ROUND(SUM(t.amount), 2) AS total_amount,
+            ROUND(AVG(t.amount), 2) AS avg_amount
+        FROM customers c
+        LEFT JOIN transactions t ON c.customer_id = t.customer_id
+        GROUP BY c.customer_id, customer_name, c.city
+        ORDER BY transaction_count DESC
+        LIMIT 10
+    """)
+    print("\nTop 10 customers by transaction count:")
+    for row in cursor.fetchall():
+        print(f"  {row[0]} | {row[1]} | {row[2]} | {row[3]} txns | Total: £{row[4]} | Avg: £{row[5]}")
+
+
+def main() -> None:
+    """Main function to create database and load data."""
+    scripts_dir = Path(__file__).parent
+    data_dir = scripts_dir.parent / "data"
+    db_path = data_dir / "santander_bank.db"
+    customers_excel = data_dir / "santander_customers.xlsx"
+    transactions_excel = data_dir / "santander_transactions.xlsx"
+
+    if db_path.exists():
+        db_path.unlink()
+        print(f"Removed existing database: {db_path}")
+
+    conn = create_database(str(db_path))
+
+    try:
+        create_customers_table(conn)
+        create_transactions_table(conn)
+
+        load_customers_data(conn, str(customers_excel))
+        load_transactions_data(conn, str(transactions_excel))
+
+        verify_data(conn)
+
+    finally:
+        conn.close()
+        print(f"\nDatabase created successfully: {db_path}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/query_1_customer_demographics.sql b/scripts/query_1_customer_demographics.sql
new file mode 100644
index 00000000..e31e2388
--- /dev/null
+++ b/scripts/query_1_customer_demographics.sql
@@ -0,0 +1,13 @@
+-- Customer Demographics by Segment
+-- Shows count, average age, and average balance for each customer segment
+
+SELECT 
+    customer_segment,
+    COUNT(*) AS customer_count,
+    ROUND(AVG(age), 1) AS avg_age,
+    ROUND(AVG(balance), 2) AS avg_balance,
+    ROUND(MIN(balance), 2) AS min_balance,
+    ROUND(MAX(balance), 2) AS max_balance
+FROM customers
+GROUP BY customer_segment
+ORDER BY customer_count DESC;
diff --git a/scripts/query_2_monthly_transactions.sql b/scripts/query_2_monthly_transactions.sql
new file mode 100644
index 00000000..1be03ea8
--- /dev/null
+++ b/scripts/query_2_monthly_transactions.sql
@@ -0,0 +1,12 @@
+-- Monthly Transaction Volume by Category
+-- Shows transaction count and total amount per category per month
+
+SELECT 
+    strftime('%Y-%m', transaction_date) AS month,
+    category,
+    COUNT(*) AS transaction_count,
+    ROUND(SUM(amount), 2) AS total_amount,
+    ROUND(AVG(amount), 2) AS avg_amount
+FROM transactions
+GROUP BY month, category
+ORDER BY month DESC, total_amount DESC;
diff --git a/scripts/query_3_top_customers.sql b/scripts/query_3_top_customers.sql
new file mode 100644
index 00000000..0ca1c51f
--- /dev/null
+++ b/scripts/query_3_top_customers.sql
@@ -0,0 +1,17 @@
+-- Top 10 Customers by Transaction Count
+-- Shows customers with the most transactions, including their details
+
+SELECT 
+    c.customer_id,
+    c.first_name || ' ' || c.last_name AS customer_name,
+    c.city,
+    c.customer_segment,
+    c.balance AS account_balance,
+    COUNT(t.transaction_id) AS transaction_count,
+    ROUND(SUM(t.amount), 2) AS total_transaction_amount,
+    ROUND(AVG(t.amount), 2) AS avg_transaction_amount
+FROM customers c
+LEFT JOIN transactions t ON c.customer_id = t.customer_id
+GROUP BY c.customer_id, customer_name, c.city, c.customer_segment, c.balance
+ORDER BY transaction_count DESC
+LIMIT 10;
diff --git a/scripts/query_4_channel_analysis.sql b/scripts/query_4_channel_analysis.sql
new file mode 100644
index 00000000..285a9e05
--- /dev/null
+++ b/scripts/query_4_channel_analysis.sql
@@ -0,0 +1,13 @@
+-- Average Transaction Amount by Channel
+-- Shows average, min, max, and total amounts for each transaction channel
+
+SELECT 
+    channel,
+    COUNT(*) AS transaction_count,
+    ROUND(AVG(amount), 2) AS avg_amount,
+    ROUND(MIN(amount), 2) AS min_amount,
+    ROUND(MAX(amount), 2) AS max_amount,
+    ROUND(SUM(amount), 2) AS total_amount
+FROM transactions
+GROUP BY channel
+ORDER BY avg_amount DESC;