diff --git a/.ipynb_checkpoints/main-checkpoint.ipynb b/.ipynb_checkpoints/main-checkpoint.ipynb
new file mode 100644
index 0000000..1c3643e
--- /dev/null
+++ b/.ipynb_checkpoints/main-checkpoint.ipynb
@@ -0,0 +1,307 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "query = \"\"\"\n",
+    "    select  final.CUSTOMER_NUMBER_main as Focal_id,\n",
+    "        CAST(final.Cash_deposit_total AS DECIMAL(18, 2)) AS Cash_deposit_total,\n",
+    "        final.Cash_deposit_count,\n",
+    "        final.SEGMENT,\n",
+    "        final.RISK,\n",
+    "        final.SAR_FLAG\n",
+    "from \n",
+    "(\n",
+    "    (\n",
+    "        select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main,\n",
+    "               subquery.Cash_deposit_total,\n",
+    "               subquery.Cash_deposit_count\n",
+    "        from \n",
+    "        (\n",
+    "            select customer_number as CUSTOMER_NUMBER_1, \n",
+    "                   sum(transaction_amount) as Cash_deposit_total, \n",
+    "                   count(*) as Cash_deposit_count\n",
+    "            from \n",
+    "            (\n",
+    "                select * \n",
+    "                from {trans_data} trans_table \n",
+    "                left join {acc_data} acc_table\n",
+    "                on trans_table.benef_account_number = acc_table.account_number\n",
+    "            ) trans\n",
+    "            where account_number not in ('None')\n",
+    "            and transaction_desc = 'CASH RELATED TRANSACTION'\n",
+    "            group by customer_number\n",
+    "        ) subquery\n",
+    "    ) main \n",
+    "    left join \n",
+    "   (\n",
+    "        select cd.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,\n",
+    "               cd.SEGMENT,\n",
+    "               cd.RISK,\n",
+    "               case\n",
+    "                    when ad.SAR_FLAG is NULL then 'N'\n",
+    "                    else ad.SAR_FLAG\n",
+    "               end as SAR_FLAG    \n",
+    "        from\n",
+    "        (\n",
+    "            select customer_number as CUSTOMER_NUMBER_3, \n",
+    "                   business_segment as SEGMENT,\n",
+    "                   case\n",
+    "                       when RISK_CLASSIFICATION = 1 then 'Low Risk'\n",
+    "                       when RISK_CLASSIFICATION = 2 then 'Medium Risk'\n",
+    "                       when RISK_CLASSIFICATION = 3 then 'High Risk'\n",
+    "                       else 'Unknown Risk'\n",
+    "                   end AS RISK\n",
+    "            from {cust_data}\n",
+    "        ) cd \n",
+    "        left join\n",
+    "        (\n",
+    "            select customer_number as CUSTOMER_NUMBER_4, \n",
+    "                   sar_flag as SAR_FLAG\n",
+    "            from {alert_data}\n",
+    "        ) ad \n",
+    "        on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4\n",
+    "    ) as cust_alert\n",
+    "    on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main\n",
+    ") as final\n",
+    "\"\"\"\n",
+    "\n",
+    "from tms_data_interface import SQLQueryInterface\n",
+    "\n",
+    "class Scenario:\n",
+    "    seq = SQLQueryInterface(schema=\"transactionschema\")\n",
+    "\n",
+    "    def logic(self, **kwargs):\n",
+    "        row_list = self.seq.execute_raw(query.format(trans_data=\"transaction10m\",\n",
+    "                                                    cust_data=\"customer_data_v1\",\n",
+    "                                                    acc_data=\"account_data_v1\",\n",
+    "                                                    alert_data=\"alert_data_v1\")\n",
+    "                                       )\n",
+    "        cols = [\"Focal_id\", \"Cash_deposit_total\", \"Cash_deposit_count\",\n",
+    "                \"Segment\", \"Risk\", \"SAR_FLAG\"]\n",
+    "        df = pd.DataFrame(row_list, columns = cols)\n",
+    "        df[\"Cash_deposit_total\"] = df[\"Cash_deposit_total\"].astype(float)\n",
+    "        return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1f20337b-8116-47e5-8743-1ba41e2df819",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Focal_id</th>\n",
+       "      <th>Cash_deposit_total</th>\n",
+       "      <th>Cash_deposit_count</th>\n",
+       "      <th>Segment</th>\n",
+       "      <th>Risk</th>\n",
+       "      <th>SAR_FLAG</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>PN469304</td>\n",
+       "      <td>8049952.0</td>\n",
+       "      <td>141</td>\n",
+       "      <td>Mass Market</td>\n",
+       "      <td>High Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>PN605743</td>\n",
+       "      <td>9766101.0</td>\n",
+       "      <td>175</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>PN399215</td>\n",
+       "      <td>8469943.0</td>\n",
+       "      <td>164</td>\n",
+       "      <td>Mass Market</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>PN175020</td>\n",
+       "      <td>17724959.0</td>\n",
+       "      <td>313</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>PN345085</td>\n",
+       "      <td>7518628.0</td>\n",
+       "      <td>124</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9005</th>\n",
+       "      <td>PN660329</td>\n",
+       "      <td>8528178.0</td>\n",
+       "      <td>141</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9006</th>\n",
+       "      <td>PN336833</td>\n",
+       "      <td>8475036.0</td>\n",
+       "      <td>150</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9007</th>\n",
+       "      <td>PN428534</td>\n",
+       "      <td>7871170.0</td>\n",
+       "      <td>129</td>\n",
+       "      <td>Priority Banking</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9008</th>\n",
+       "      <td>PN101660</td>\n",
+       "      <td>8450309.0</td>\n",
+       "      <td>142</td>\n",
+       "      <td>Mass Market</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9009</th>\n",
+       "      <td>PN198641</td>\n",
+       "      <td>8690226.0</td>\n",
+       "      <td>166</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9010 rows × 6 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Focal_id  Cash_deposit_total  Cash_deposit_count           Segment  \\\n",
+       "0     PN469304           8049952.0                 141       Mass Market   \n",
+       "1     PN605743           9766101.0                 175            Others   \n",
+       "2     PN399215           8469943.0                 164       Mass Market   \n",
+       "3     PN175020          17724959.0                 313            Others   \n",
+       "4     PN345085           7518628.0                 124            Others   \n",
+       "...        ...                 ...                 ...               ...   \n",
+       "9005  PN660329           8528178.0                 141            Others   \n",
+       "9006  PN336833           8475036.0                 150            Others   \n",
+       "9007  PN428534           7871170.0                 129  Priority Banking   \n",
+       "9008  PN101660           8450309.0                 142       Mass Market   \n",
+       "9009  PN198641           8690226.0                 166            Others   \n",
+       "\n",
+       "             Risk SAR_FLAG  \n",
+       "0       High Risk        N  \n",
+       "1        Low Risk        N  \n",
+       "2        Low Risk        N  \n",
+       "3        Low Risk        N  \n",
+       "4     Medium Risk        N  \n",
+       "...           ...      ...  \n",
+       "9005     Low Risk        N  \n",
+       "9006     Low Risk        N  \n",
+       "9007     Low Risk        N  \n",
+       "9008     Low Risk        N  \n",
+       "9009     Low Risk        N  \n",
+       "\n",
+       "[9010 rows x 6 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# sen = Scenario()\n",
+    "# sen.logic()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6de62b37-00d1-4c88-b27b-9a70e05add91",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/main.ipynb b/main.ipynb
index 3277afb..1c3643e 100644
--- a/main.ipynb
+++ b/main.ipynb
@@ -1,33 +1,307 @@
-{
-    "cells": [
-        {
-            "cell_type": "code",
-            "execution_count": null,
-            "id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0",
-            "metadata": {},
-            "outputs": [],
-            "source": "from tms_data_interface import SQLQueryInterface\n\nclass Scenario:\n\tseq = SQLQueryInterface()\n\n\tdef logic(self, **kwargs):\n\t\t# Write your code here\n"
-        }
-    ],
-    "metadata": {
-        "kernelspec": {
-            "display_name": "Python 3 (ipykernel)",
-            "language": "python",
-            "name": "python3"
-        },
-        "language_info": {
-            "codemirror_mode": {
-                "name": "ipython",
-                "version": 3
-            },
-            "file_extension": ".py",
-            "mimetype": "text/x-python",
-            "name": "python",
-            "nbconvert_exporter": "python",
-            "pygments_lexer": "ipython3",
-            "version": "3.8.13"
-        }
-    },
-    "nbformat": 4,
-    "nbformat_minor": 5
-}
\ No newline at end of file
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "query = \"\"\"\n",
+    "    select  final.CUSTOMER_NUMBER_main as Focal_id,\n",
+    "        CAST(final.Cash_deposit_total AS DECIMAL(18, 2)) AS Cash_deposit_total,\n",
+    "        final.Cash_deposit_count,\n",
+    "        final.SEGMENT,\n",
+    "        final.RISK,\n",
+    "        final.SAR_FLAG\n",
+    "from \n",
+    "(\n",
+    "    (\n",
+    "        select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main,\n",
+    "               subquery.Cash_deposit_total,\n",
+    "               subquery.Cash_deposit_count\n",
+    "        from \n",
+    "        (\n",
+    "            select customer_number as CUSTOMER_NUMBER_1, \n",
+    "                   sum(transaction_amount) as Cash_deposit_total, \n",
+    "                   count(*) as Cash_deposit_count\n",
+    "            from \n",
+    "            (\n",
+    "                select * \n",
+    "                from {trans_data} trans_table \n",
+    "                left join {acc_data} acc_table\n",
+    "                on trans_table.benef_account_number = acc_table.account_number\n",
+    "            ) trans\n",
+    "            where account_number not in ('None')\n",
+    "            and transaction_desc = 'CASH RELATED TRANSACTION'\n",
+    "            group by customer_number\n",
+    "        ) subquery\n",
+    "    ) main \n",
+    "    left join \n",
+    "   (\n",
+    "        select cd.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,\n",
+    "               cd.SEGMENT,\n",
+    "               cd.RISK,\n",
+    "               case\n",
+    "                    when ad.SAR_FLAG is NULL then 'N'\n",
+    "                    else ad.SAR_FLAG\n",
+    "               end as SAR_FLAG    \n",
+    "        from\n",
+    "        (\n",
+    "            select customer_number as CUSTOMER_NUMBER_3, \n",
+    "                   business_segment as SEGMENT,\n",
+    "                   case\n",
+    "                       when RISK_CLASSIFICATION = 1 then 'Low Risk'\n",
+    "                       when RISK_CLASSIFICATION = 2 then 'Medium Risk'\n",
+    "                       when RISK_CLASSIFICATION = 3 then 'High Risk'\n",
+    "                       else 'Unknown Risk'\n",
+    "                   end AS RISK\n",
+    "            from {cust_data}\n",
+    "        ) cd \n",
+    "        left join\n",
+    "        (\n",
+    "            select customer_number as CUSTOMER_NUMBER_4, \n",
+    "                   sar_flag as SAR_FLAG\n",
+    "            from {alert_data}\n",
+    "        ) ad \n",
+    "        on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4\n",
+    "    ) as cust_alert\n",
+    "    on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main\n",
+    ") as final\n",
+    "\"\"\"\n",
+    "\n",
+    "from tms_data_interface import SQLQueryInterface\n",
+    "\n",
+    "class Scenario:\n",
+    "    seq = SQLQueryInterface(schema=\"transactionschema\")\n",
+    "\n",
+    "    def logic(self, **kwargs):\n",
+    "        row_list = self.seq.execute_raw(query.format(trans_data=\"transaction10m\",\n",
+    "                                                    cust_data=\"customer_data_v1\",\n",
+    "                                                    acc_data=\"account_data_v1\",\n",
+    "                                                    alert_data=\"alert_data_v1\")\n",
+    "                                       )\n",
+    "        cols = [\"Focal_id\", \"Cash_deposit_total\", \"Cash_deposit_count\",\n",
+    "                \"Segment\", \"Risk\", \"SAR_FLAG\"]\n",
+    "        df = pd.DataFrame(row_list, columns = cols)\n",
+    "        df[\"Cash_deposit_total\"] = df[\"Cash_deposit_total\"].astype(float)\n",
+    "        return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1f20337b-8116-47e5-8743-1ba41e2df819",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Focal_id</th>\n",
+       "      <th>Cash_deposit_total</th>\n",
+       "      <th>Cash_deposit_count</th>\n",
+       "      <th>Segment</th>\n",
+       "      <th>Risk</th>\n",
+       "      <th>SAR_FLAG</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>PN469304</td>\n",
+       "      <td>8049952.0</td>\n",
+       "      <td>141</td>\n",
+       "      <td>Mass Market</td>\n",
+       "      <td>High Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>PN605743</td>\n",
+       "      <td>9766101.0</td>\n",
+       "      <td>175</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>PN399215</td>\n",
+       "      <td>8469943.0</td>\n",
+       "      <td>164</td>\n",
+       "      <td>Mass Market</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>PN175020</td>\n",
+       "      <td>17724959.0</td>\n",
+       "      <td>313</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>PN345085</td>\n",
+       "      <td>7518628.0</td>\n",
+       "      <td>124</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9005</th>\n",
+       "      <td>PN660329</td>\n",
+       "      <td>8528178.0</td>\n",
+       "      <td>141</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9006</th>\n",
+       "      <td>PN336833</td>\n",
+       "      <td>8475036.0</td>\n",
+       "      <td>150</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9007</th>\n",
+       "      <td>PN428534</td>\n",
+       "      <td>7871170.0</td>\n",
+       "      <td>129</td>\n",
+       "      <td>Priority Banking</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9008</th>\n",
+       "      <td>PN101660</td>\n",
+       "      <td>8450309.0</td>\n",
+       "      <td>142</td>\n",
+       "      <td>Mass Market</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9009</th>\n",
+       "      <td>PN198641</td>\n",
+       "      <td>8690226.0</td>\n",
+       "      <td>166</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>9010 rows × 6 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Focal_id  Cash_deposit_total  Cash_deposit_count           Segment  \\\n",
+       "0     PN469304           8049952.0                 141       Mass Market   \n",
+       "1     PN605743           9766101.0                 175            Others   \n",
+       "2     PN399215           8469943.0                 164       Mass Market   \n",
+       "3     PN175020          17724959.0                 313            Others   \n",
+       "4     PN345085           7518628.0                 124            Others   \n",
+       "...        ...                 ...                 ...               ...   \n",
+       "9005  PN660329           8528178.0                 141            Others   \n",
+       "9006  PN336833           8475036.0                 150            Others   \n",
+       "9007  PN428534           7871170.0                 129  Priority Banking   \n",
+       "9008  PN101660           8450309.0                 142       Mass Market   \n",
+       "9009  PN198641           8690226.0                 166            Others   \n",
+       "\n",
+       "             Risk SAR_FLAG  \n",
+       "0       High Risk        N  \n",
+       "1        Low Risk        N  \n",
+       "2        Low Risk        N  \n",
+       "3        Low Risk        N  \n",
+       "4     Medium Risk        N  \n",
+       "...           ...      ...  \n",
+       "9005     Low Risk        N  \n",
+       "9006     Low Risk        N  \n",
+       "9007     Low Risk        N  \n",
+       "9008     Low Risk        N  \n",
+       "9009     Low Risk        N  \n",
+       "\n",
+       "[9010 rows x 6 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# sen = Scenario()\n",
+    "# sen.logic()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6de62b37-00d1-4c88-b27b-9a70e05add91",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/main.py b/main.py
new file mode 100644
index 0000000..121063e
--- /dev/null
+++ b/main.py
@@ -0,0 +1,101 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[2]:
+
+
+import pandas as pd
+
+query = """
+    select  final.CUSTOMER_NUMBER_main as Focal_id,
+        CAST(final.Cash_deposit_total AS DECIMAL(18, 2)) AS Cash_deposit_total,
+        final.Cash_deposit_count,
+        final.SEGMENT,
+        final.RISK,
+        final.SAR_FLAG
+from 
+(
+    (
+        select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main,
+               subquery.Cash_deposit_total,
+               subquery.Cash_deposit_count
+        from 
+        (
+            select customer_number as CUSTOMER_NUMBER_1, 
+                   sum(transaction_amount) as Cash_deposit_total, 
+                   count(*) as Cash_deposit_count
+            from 
+            (
+                select * 
+                from {trans_data} trans_table 
+                left join {acc_data} acc_table
+                on trans_table.benef_account_number = acc_table.account_number
+            ) trans
+            where account_number not in ('None')
+            and transaction_desc = 'CASH RELATED TRANSACTION'
+            group by customer_number
+        ) subquery
+    ) main 
+    left join 
+   (
+        select cd.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,
+               cd.SEGMENT,
+               cd.RISK,
+               case
+                    when ad.SAR_FLAG is NULL then 'N'
+                    else ad.SAR_FLAG
+               end as SAR_FLAG    
+        from
+        (
+            select customer_number as CUSTOMER_NUMBER_3, 
+                   business_segment as SEGMENT,
+                   case
+                       when RISK_CLASSIFICATION = 1 then 'Low Risk'
+                       when RISK_CLASSIFICATION = 2 then 'Medium Risk'
+                       when RISK_CLASSIFICATION = 3 then 'High Risk'
+                       else 'Unknown Risk'
+                   end AS RISK
+            from {cust_data}
+        ) cd 
+        left join
+        (
+            select customer_number as CUSTOMER_NUMBER_4, 
+                   sar_flag as SAR_FLAG
+            from {alert_data}
+        ) ad 
+        on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4
+    ) as cust_alert
+    on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main
+) as final
+"""
+
+from tms_data_interface import SQLQueryInterface
+
+class Scenario:
+    seq = SQLQueryInterface(schema="transactionschema")
+
+    def logic(self, **kwargs):
+        row_list = self.seq.execute_raw(query.format(trans_data="transaction10m",
+                                                    cust_data="customer_data_v1",
+                                                    acc_data="account_data_v1",
+                                                    alert_data="alert_data_v1")
+                                       )
+        cols = ["Focal_id", "Cash_deposit_total", "Cash_deposit_count",
+                "Segment", "Risk", "SAR_FLAG"]
+        df = pd.DataFrame(row_list, columns = cols)
+        df["Cash_deposit_total"] = df["Cash_deposit_total"].astype(float)
+        return df
+
+
+# In[3]:
+
+
+# sen = Scenario()
+# sen.logic()
+
+
+# In[ ]:
+
+
+
+