diff --git a/Scripts/Generate_transactions.py b/Scripts/Generate_transactions.py
deleted file mode 100644
index f3e3712..0000000
--- a/Scripts/Generate_transactions.py
+++ /dev/null
@@ -1,115 +0,0 @@
-from faker import Faker
-from dotenv import load_dotenv
-from datetime import datetime
-import os
-import random
-import pandas as pd
-import boto3
-
-# ---- Setup ----
-fake = Faker()
-load_dotenv()
-
-s3 = boto3.resource(
-    "s3",
-    endpoint_url=os.getenv("STORAGE_ENDPOINT"),
-    aws_access_key_id=os.getenv("STORAGE_ACCESS_KEY"),
-    aws_secret_access_key=os.getenv("STORAGE_SECRET_KEY")
-)
-
-bucket_name = os.getenv("STORAGE_BUCKET")
-accounts_key = "DataLab/accounts/accounts.csv"
-transactions_s3_key = "DataLab/transactions/transactions.csv"
-
-# ---- Ensure local data folder exists ----
-os.makedirs("../Data", exist_ok=True)
-
-# ---- Download accounts.csv from S3 ----
-local_accounts_file = "../Data/accounts.csv"
-try:
-    s3.Bucket(bucket_name).download_file(accounts_key, local_accounts_file)
-    print("Downloaded accounts.csv from S3.")
-except Exception as e:
-    print("ERROR: Could not download accounts.csv:", e)
-    raise SystemExit()
-
-# ---- Load accounts DataFrame ----
-accounts_df = pd.read_csv(local_accounts_file)
-
-# ---- Sample vendors ----
-vendors = ["Amazon", "Walmart", "Target", "Starbucks", "Apple", "Netflix", "Uber", "Lyft", "BestBuy", "Costco"]
-
-# ---- Helper Functions ----
-def generate_transaction_id(account_id, idx):
-    """Generate a unique transaction ID combining account ID and index."""
-    return f"{account_id}{str(idx).zfill(5)}"
-
-def generate_transaction(account):
-    """Generate a realistic transaction for a given account."""
-    t_type = random.choices(
-        ["Deposit", "Withdrawal", "Payment", "Transfer"], 
-        weights=[0.4, 0.3, 0.2, 0.1], k=1
-    )[0]
-
-    transaction_data = {
-        "transaction_id": None,  # fill later
-        "account_id": account['account_id'],
-        "branch_id": None,
-        "transaction_type": t_type,
-        "amount": 0,
-        "date": fake.date_between(start_date=pd.to_datetime(account['open_date']), end_date=datetime.today()),
-        "balance_after": 0,
-        "vendor": None,
-        "transaction_location": None
-    }
-
-    if t_type in ["Deposit", "Withdrawal"]:
-        # Pick one of the branches for deposit/withdrawal
-        transaction_data["branch_id"] = account['branch_id']
-        amount = round(random.uniform(50, 7000), 2) if t_type == "Withdrawal" else round(random.uniform(20, 10000), 2)
-        if t_type == "Withdrawal":
-            amount = min(amount, account['balance'])
-            account['balance'] -= amount
-        else:
-            account['balance'] += amount
-        transaction_data["amount"] = amount
-        transaction_data["balance_after"] = round(account['balance'], 2)
-        transaction_data["transaction_location"] = f"Branch {account['branch_id']}"
-
-    else:  # Payment or Transfer
-        transaction_data["branch_id"] = None
-        transaction_data["vendor"] = random.choice(vendors)
-        amount = round(random.uniform(5, 1000), 2)
-        account['balance'] = max(account['balance'] - amount, 0)
-        transaction_data["amount"] = amount
-        transaction_data["balance_after"] = round(account['balance'], 2)
-        transaction_data["transaction_location"] = "POS / Online"
-
-    return transaction_data
-
-# ---- Generate transactions ----
-transactions = []
-idx = 1
-
-for _, account in accounts_df.iterrows():
-    account_transactions_count = random.randint(5, 20)
-    for _ in range(account_transactions_count):
-        txn = generate_transaction(account)
-        txn['transaction_id'] = generate_transaction_id(account['account_id'], idx)
-        transactions.append(txn)
-        idx += 1
-
-# ---- Convert to DataFrame ----
-transactions_df = pd.DataFrame(transactions)
-
-# ---- Save locally ----
-local_transactions_file = "../Data/transactions.csv"
-transactions_df.to_csv(local_transactions_file, index=False)
-print("Generated transactions.csv locally with realistic branch/vendor data.")
-
-# ---- Upload to S3 ----
-try:
-    s3.Bucket(bucket_name).upload_file(local_transactions_file, transactions_s3_key)
-    print(f"Uploaded transactions.csv to s3://{bucket_name}/{transactions_s3_key}")
-except Exception as e:
-    print("ERROR: Could not upload transactions.csv to S3:", e)