diff --git a/.ipynb_checkpoints/main-checkpoint.ipynb b/.ipynb_checkpoints/main-checkpoint.ipynb
new file mode 100644
index 0000000..d4445a1
--- /dev/null
+++ b/.ipynb_checkpoints/main-checkpoint.ipynb
@@ -0,0 +1,447 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "2f9a4ca7-c066-4d93-9957-0d9145f9265d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from tms_data_interface import SQLQueryInterface\n",
+    "seq = SQLQueryInterface(schema=\"transactionschema\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "fc212ace-ca7a-45f2-8137-f436c6123652",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[['account_data_v1'],\n",
+       " ['account_data_v2'],\n",
+       " ['alert_data_v1'],\n",
+       " ['alert_data_v2'],\n",
+       " ['customer_data_v1'],\n",
+       " ['customer_data_v2'],\n",
+       " ['transaction10m'],\n",
+       " ['transaction60m']]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "seq.execute_raw(\"show tables\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "134d0b3d-5481-4975-af07-c80ab09d6dd2",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "query = \"\"\"\n",
+    "    select  final.CUSTOMER_NUMBER_main as Focal_id,\n",
+    "            final.Credit_transaction_amount,\n",
+    "            final.Total_no_of_credit_transactions,\n",
+    "            final.Debit_transaction_amount,\n",
+    "            final.Total_no_of_debit_transactions,\n",
+    "            final.Wash_Ratio,\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.Credit_transaction_amount,\n",
+    "                    subquery.Total_no_of_credit_transactions,\n",
+    "                    case\n",
+    "                         when subquery.Debit_transaction_amount is NULL then 0\n",
+    "                         else Debit_transaction_amount\n",
+    "                    end as Debit_transaction_amount,\n",
+    "                    case\n",
+    "                         when subquery.Total_no_of_debit_transactions is NULL then 0\n",
+    "                         else Total_no_of_debit_transactions\n",
+    "                    end as Total_no_of_debit_transactions,\n",
+    "                    case\n",
+    "                         when subquery.Debit_transaction_amount = 0\n",
+    "                         or subquery.Debit_transaction_amount is NULL then 0\n",
+    "                         else subquery.Credit_transaction_amount / subquery.Debit_transaction_amount\n",
+    "                    end as Wash_Ratio\n",
+    "            from \n",
+    "            (\n",
+    "                (\n",
+    "                    select customer_number as CUSTOMER_NUMBER_1, \n",
+    "                            sum(transaction_amount) as Credit_transaction_amount, \n",
+    "                            count(*) as Total_no_of_credit_transactions\n",
+    "                    from \n",
+    "                    (\n",
+    "                        select * \n",
+    "                        from {trans_data} as trans_table left join {acc_data} as acc_table\n",
+    "                        on trans_table.benef_account_number = acc_table.account_number\n",
+    "                    )\n",
+    "                    where account_number not in ('None')\n",
+    "                    group by 1\n",
+    "                ) credit left join\n",
+    "                (\n",
+    "                    select customer_number as CUSTOMER_NUMBER_2, \n",
+    "                            sum(transaction_amount) as Debit_transaction_amount, \n",
+    "                            count(*) as Total_no_of_debit_transactions\n",
+    "                    from \n",
+    "                    (\n",
+    "                        select * \n",
+    "                        from {trans_data} as trans_table left join {acc_data} as acc_table\n",
+    "                        on trans_table.orig_account_number = acc_table.account_number\n",
+    "                    )\n",
+    "                    where account_number not in ('None')\n",
+    "                    group by 1\n",
+    "                ) debit on credit.CUSTOMER_NUMBER_1 = debit.CUSTOMER_NUMBER_2 \n",
+    "            ) subquery\n",
+    "        ) main left join \n",
+    "        (\n",
+    "            select subquery.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,\n",
+    "                    subquery.SEGMENT,\n",
+    "                    subquery.RISK,\n",
+    "                    case\n",
+    "                         when subquery.SAR_FLAG is NULL then 'N'\n",
+    "                         else subquery.SAR_FLAG\n",
+    "                    end as SAR_FLAG    \n",
+    "            from\n",
+    "            (\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 left join\n",
+    "                (\n",
+    "                    select customer_number as CUSTOMER_NUMBER_4, \n",
+    "                            sar_flag as SAR_FLAG\n",
+    "                    from {alert_data}\n",
+    "                ) ad on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4\n",
+    "            ) subquery\n",
+    "        ) cust_alert on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main\n",
+    "    ) final\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d220561a-34c9-48d2-8e2f-5d174a87540b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "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\", \"Credit_transaction_amount\",\n",
+    "                \"Total_no_of_credit_transactions\",\n",
+    "                \"Debit_transaction_amount\", \"Total_no_of_debit_transactions\",\n",
+    "                \"Wash_Ratio\", \"Segment\", \"Risk\", \"SAR_FLAG\"]\n",
+    "        df = pd.DataFrame(row_list, columns = cols)\n",
+    "        return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "2e5a0ea9-64cd-4a8d-9a5d-e5e7b36a401a",
+   "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>Credit_transaction_amount</th>\n",
+       "      <th>Total_no_of_credit_transactions</th>\n",
+       "      <th>Debit_transaction_amount</th>\n",
+       "      <th>Total_no_of_debit_transactions</th>\n",
+       "      <th>Wash_Ratio</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>PN808624</td>\n",
+       "      <td>4.601504e+09</td>\n",
+       "      <td>3239</td>\n",
+       "      <td>4.461280e+09</td>\n",
+       "      <td>3129</td>\n",
+       "      <td>1.031431</td>\n",
+       "      <td>Corporate Banking</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>PN663041</td>\n",
+       "      <td>2.106224e+09</td>\n",
+       "      <td>1573</td>\n",
+       "      <td>2.281829e+09</td>\n",
+       "      <td>1563</td>\n",
+       "      <td>0.923042</td>\n",
+       "      <td>Corporate Banking</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>PN525913</td>\n",
+       "      <td>1.057799e+09</td>\n",
+       "      <td>776</td>\n",
+       "      <td>1.223876e+09</td>\n",
+       "      <td>850</td>\n",
+       "      <td>0.864302</td>\n",
+       "      <td>Whole Sale Banking</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>PN440274</td>\n",
+       "      <td>4.806265e+09</td>\n",
+       "      <td>3506</td>\n",
+       "      <td>4.972813e+09</td>\n",
+       "      <td>3599</td>\n",
+       "      <td>0.966508</td>\n",
+       "      <td>Whole Sale Banking</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>PN213026</td>\n",
+       "      <td>3.982349e+09</td>\n",
+       "      <td>2809</td>\n",
+       "      <td>4.122674e+09</td>\n",
+       "      <td>2783</td>\n",
+       "      <td>0.965963</td>\n",
+       "      <td>Whole Sale Banking</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10009</th>\n",
+       "      <td>PN774741</td>\n",
+       "      <td>3.373466e+07</td>\n",
+       "      <td>250</td>\n",
+       "      <td>2.443148e+07</td>\n",
+       "      <td>381</td>\n",
+       "      <td>1.380787</td>\n",
+       "      <td>Priority Banking</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10010</th>\n",
+       "      <td>PN868326</td>\n",
+       "      <td>3.785344e+07</td>\n",
+       "      <td>259</td>\n",
+       "      <td>2.408309e+07</td>\n",
+       "      <td>352</td>\n",
+       "      <td>1.571785</td>\n",
+       "      <td>Ultra High NetWorth</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>Y</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10011</th>\n",
+       "      <td>PN667837</td>\n",
+       "      <td>3.330357e+07</td>\n",
+       "      <td>256</td>\n",
+       "      <td>2.676301e+07</td>\n",
+       "      <td>359</td>\n",
+       "      <td>1.244388</td>\n",
+       "      <td>Mass Market</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10012</th>\n",
+       "      <td>PN809566</td>\n",
+       "      <td>3.890076e+07</td>\n",
+       "      <td>276</td>\n",
+       "      <td>2.554121e+07</td>\n",
+       "      <td>400</td>\n",
+       "      <td>1.523059</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10013</th>\n",
+       "      <td>PN739647</td>\n",
+       "      <td>3.505184e+07</td>\n",
+       "      <td>223</td>\n",
+       "      <td>2.232980e+07</td>\n",
+       "      <td>381</td>\n",
+       "      <td>1.569734</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10014 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Focal_id  Credit_transaction_amount  Total_no_of_credit_transactions  \\\n",
+       "0      PN808624               4.601504e+09                             3239   \n",
+       "1      PN663041               2.106224e+09                             1573   \n",
+       "2      PN525913               1.057799e+09                              776   \n",
+       "3      PN440274               4.806265e+09                             3506   \n",
+       "4      PN213026               3.982349e+09                             2809   \n",
+       "...         ...                        ...                              ...   \n",
+       "10009  PN774741               3.373466e+07                              250   \n",
+       "10010  PN868326               3.785344e+07                              259   \n",
+       "10011  PN667837               3.330357e+07                              256   \n",
+       "10012  PN809566               3.890076e+07                              276   \n",
+       "10013  PN739647               3.505184e+07                              223   \n",
+       "\n",
+       "       Debit_transaction_amount  Total_no_of_debit_transactions  Wash_Ratio  \\\n",
+       "0                  4.461280e+09                            3129    1.031431   \n",
+       "1                  2.281829e+09                            1563    0.923042   \n",
+       "2                  1.223876e+09                             850    0.864302   \n",
+       "3                  4.972813e+09                            3599    0.966508   \n",
+       "4                  4.122674e+09                            2783    0.965963   \n",
+       "...                         ...                             ...         ...   \n",
+       "10009              2.443148e+07                             381    1.380787   \n",
+       "10010              2.408309e+07                             352    1.571785   \n",
+       "10011              2.676301e+07                             359    1.244388   \n",
+       "10012              2.554121e+07                             400    1.523059   \n",
+       "10013              2.232980e+07                             381    1.569734   \n",
+       "\n",
+       "                   Segment         Risk SAR_FLAG  \n",
+       "0        Corporate Banking  Medium Risk        N  \n",
+       "1        Corporate Banking     Low Risk        N  \n",
+       "2       Whole Sale Banking     Low Risk        N  \n",
+       "3       Whole Sale Banking  Medium Risk        N  \n",
+       "4       Whole Sale Banking  Medium Risk        N  \n",
+       "...                    ...          ...      ...  \n",
+       "10009     Priority Banking  Medium Risk        N  \n",
+       "10010  Ultra High NetWorth  Medium Risk        Y  \n",
+       "10011          Mass Market  Medium Risk        N  \n",
+       "10012               Others     Low Risk        N  \n",
+       "10013               Others     Low Risk        N  \n",
+       "\n",
+       "[10014 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# sen = Scenario()\n",
+    "# sen.logic()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "150bb5ce-6be1-44fc-a606-6d375354626d",
+   "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..d4445a1 100644
--- a/main.ipynb
+++ b/main.ipynb
@@ -1,33 +1,447 @@
-{
-    "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": 1,
+   "id": "e706cfb0-2234-4c4c-95d8-d1968f656aa0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "2f9a4ca7-c066-4d93-9957-0d9145f9265d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from tms_data_interface import SQLQueryInterface\n",
+    "seq = SQLQueryInterface(schema=\"transactionschema\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "fc212ace-ca7a-45f2-8137-f436c6123652",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[['account_data_v1'],\n",
+       " ['account_data_v2'],\n",
+       " ['alert_data_v1'],\n",
+       " ['alert_data_v2'],\n",
+       " ['customer_data_v1'],\n",
+       " ['customer_data_v2'],\n",
+       " ['transaction10m'],\n",
+       " ['transaction60m']]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "seq.execute_raw(\"show tables\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "134d0b3d-5481-4975-af07-c80ab09d6dd2",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "query = \"\"\"\n",
+    "    select  final.CUSTOMER_NUMBER_main as Focal_id,\n",
+    "            final.Credit_transaction_amount,\n",
+    "            final.Total_no_of_credit_transactions,\n",
+    "            final.Debit_transaction_amount,\n",
+    "            final.Total_no_of_debit_transactions,\n",
+    "            final.Wash_Ratio,\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.Credit_transaction_amount,\n",
+    "                    subquery.Total_no_of_credit_transactions,\n",
+    "                    case\n",
+    "                         when subquery.Debit_transaction_amount is NULL then 0\n",
+    "                         else Debit_transaction_amount\n",
+    "                    end as Debit_transaction_amount,\n",
+    "                    case\n",
+    "                         when subquery.Total_no_of_debit_transactions is NULL then 0\n",
+    "                         else Total_no_of_debit_transactions\n",
+    "                    end as Total_no_of_debit_transactions,\n",
+    "                    case\n",
+    "                         when subquery.Debit_transaction_amount = 0\n",
+    "                         or subquery.Debit_transaction_amount is NULL then 0\n",
+    "                         else subquery.Credit_transaction_amount / subquery.Debit_transaction_amount\n",
+    "                    end as Wash_Ratio\n",
+    "            from \n",
+    "            (\n",
+    "                (\n",
+    "                    select customer_number as CUSTOMER_NUMBER_1, \n",
+    "                            sum(transaction_amount) as Credit_transaction_amount, \n",
+    "                            count(*) as Total_no_of_credit_transactions\n",
+    "                    from \n",
+    "                    (\n",
+    "                        select * \n",
+    "                        from {trans_data} as trans_table left join {acc_data} as acc_table\n",
+    "                        on trans_table.benef_account_number = acc_table.account_number\n",
+    "                    )\n",
+    "                    where account_number not in ('None')\n",
+    "                    group by 1\n",
+    "                ) credit left join\n",
+    "                (\n",
+    "                    select customer_number as CUSTOMER_NUMBER_2, \n",
+    "                            sum(transaction_amount) as Debit_transaction_amount, \n",
+    "                            count(*) as Total_no_of_debit_transactions\n",
+    "                    from \n",
+    "                    (\n",
+    "                        select * \n",
+    "                        from {trans_data} as trans_table left join {acc_data} as acc_table\n",
+    "                        on trans_table.orig_account_number = acc_table.account_number\n",
+    "                    )\n",
+    "                    where account_number not in ('None')\n",
+    "                    group by 1\n",
+    "                ) debit on credit.CUSTOMER_NUMBER_1 = debit.CUSTOMER_NUMBER_2 \n",
+    "            ) subquery\n",
+    "        ) main left join \n",
+    "        (\n",
+    "            select subquery.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,\n",
+    "                    subquery.SEGMENT,\n",
+    "                    subquery.RISK,\n",
+    "                    case\n",
+    "                         when subquery.SAR_FLAG is NULL then 'N'\n",
+    "                         else subquery.SAR_FLAG\n",
+    "                    end as SAR_FLAG    \n",
+    "            from\n",
+    "            (\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 left join\n",
+    "                (\n",
+    "                    select customer_number as CUSTOMER_NUMBER_4, \n",
+    "                            sar_flag as SAR_FLAG\n",
+    "                    from {alert_data}\n",
+    "                ) ad on cd.CUSTOMER_NUMBER_3 = ad.CUSTOMER_NUMBER_4\n",
+    "            ) subquery\n",
+    "        ) cust_alert on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main\n",
+    "    ) final\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d220561a-34c9-48d2-8e2f-5d174a87540b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "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\", \"Credit_transaction_amount\",\n",
+    "                \"Total_no_of_credit_transactions\",\n",
+    "                \"Debit_transaction_amount\", \"Total_no_of_debit_transactions\",\n",
+    "                \"Wash_Ratio\", \"Segment\", \"Risk\", \"SAR_FLAG\"]\n",
+    "        df = pd.DataFrame(row_list, columns = cols)\n",
+    "        return df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "2e5a0ea9-64cd-4a8d-9a5d-e5e7b36a401a",
+   "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>Credit_transaction_amount</th>\n",
+       "      <th>Total_no_of_credit_transactions</th>\n",
+       "      <th>Debit_transaction_amount</th>\n",
+       "      <th>Total_no_of_debit_transactions</th>\n",
+       "      <th>Wash_Ratio</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>PN808624</td>\n",
+       "      <td>4.601504e+09</td>\n",
+       "      <td>3239</td>\n",
+       "      <td>4.461280e+09</td>\n",
+       "      <td>3129</td>\n",
+       "      <td>1.031431</td>\n",
+       "      <td>Corporate Banking</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>PN663041</td>\n",
+       "      <td>2.106224e+09</td>\n",
+       "      <td>1573</td>\n",
+       "      <td>2.281829e+09</td>\n",
+       "      <td>1563</td>\n",
+       "      <td>0.923042</td>\n",
+       "      <td>Corporate Banking</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>PN525913</td>\n",
+       "      <td>1.057799e+09</td>\n",
+       "      <td>776</td>\n",
+       "      <td>1.223876e+09</td>\n",
+       "      <td>850</td>\n",
+       "      <td>0.864302</td>\n",
+       "      <td>Whole Sale Banking</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>PN440274</td>\n",
+       "      <td>4.806265e+09</td>\n",
+       "      <td>3506</td>\n",
+       "      <td>4.972813e+09</td>\n",
+       "      <td>3599</td>\n",
+       "      <td>0.966508</td>\n",
+       "      <td>Whole Sale Banking</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>PN213026</td>\n",
+       "      <td>3.982349e+09</td>\n",
+       "      <td>2809</td>\n",
+       "      <td>4.122674e+09</td>\n",
+       "      <td>2783</td>\n",
+       "      <td>0.965963</td>\n",
+       "      <td>Whole Sale Banking</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10009</th>\n",
+       "      <td>PN774741</td>\n",
+       "      <td>3.373466e+07</td>\n",
+       "      <td>250</td>\n",
+       "      <td>2.443148e+07</td>\n",
+       "      <td>381</td>\n",
+       "      <td>1.380787</td>\n",
+       "      <td>Priority Banking</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10010</th>\n",
+       "      <td>PN868326</td>\n",
+       "      <td>3.785344e+07</td>\n",
+       "      <td>259</td>\n",
+       "      <td>2.408309e+07</td>\n",
+       "      <td>352</td>\n",
+       "      <td>1.571785</td>\n",
+       "      <td>Ultra High NetWorth</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>Y</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10011</th>\n",
+       "      <td>PN667837</td>\n",
+       "      <td>3.330357e+07</td>\n",
+       "      <td>256</td>\n",
+       "      <td>2.676301e+07</td>\n",
+       "      <td>359</td>\n",
+       "      <td>1.244388</td>\n",
+       "      <td>Mass Market</td>\n",
+       "      <td>Medium Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10012</th>\n",
+       "      <td>PN809566</td>\n",
+       "      <td>3.890076e+07</td>\n",
+       "      <td>276</td>\n",
+       "      <td>2.554121e+07</td>\n",
+       "      <td>400</td>\n",
+       "      <td>1.523059</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10013</th>\n",
+       "      <td>PN739647</td>\n",
+       "      <td>3.505184e+07</td>\n",
+       "      <td>223</td>\n",
+       "      <td>2.232980e+07</td>\n",
+       "      <td>381</td>\n",
+       "      <td>1.569734</td>\n",
+       "      <td>Others</td>\n",
+       "      <td>Low Risk</td>\n",
+       "      <td>N</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10014 rows × 9 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Focal_id  Credit_transaction_amount  Total_no_of_credit_transactions  \\\n",
+       "0      PN808624               4.601504e+09                             3239   \n",
+       "1      PN663041               2.106224e+09                             1573   \n",
+       "2      PN525913               1.057799e+09                              776   \n",
+       "3      PN440274               4.806265e+09                             3506   \n",
+       "4      PN213026               3.982349e+09                             2809   \n",
+       "...         ...                        ...                              ...   \n",
+       "10009  PN774741               3.373466e+07                              250   \n",
+       "10010  PN868326               3.785344e+07                              259   \n",
+       "10011  PN667837               3.330357e+07                              256   \n",
+       "10012  PN809566               3.890076e+07                              276   \n",
+       "10013  PN739647               3.505184e+07                              223   \n",
+       "\n",
+       "       Debit_transaction_amount  Total_no_of_debit_transactions  Wash_Ratio  \\\n",
+       "0                  4.461280e+09                            3129    1.031431   \n",
+       "1                  2.281829e+09                            1563    0.923042   \n",
+       "2                  1.223876e+09                             850    0.864302   \n",
+       "3                  4.972813e+09                            3599    0.966508   \n",
+       "4                  4.122674e+09                            2783    0.965963   \n",
+       "...                         ...                             ...         ...   \n",
+       "10009              2.443148e+07                             381    1.380787   \n",
+       "10010              2.408309e+07                             352    1.571785   \n",
+       "10011              2.676301e+07                             359    1.244388   \n",
+       "10012              2.554121e+07                             400    1.523059   \n",
+       "10013              2.232980e+07                             381    1.569734   \n",
+       "\n",
+       "                   Segment         Risk SAR_FLAG  \n",
+       "0        Corporate Banking  Medium Risk        N  \n",
+       "1        Corporate Banking     Low Risk        N  \n",
+       "2       Whole Sale Banking     Low Risk        N  \n",
+       "3       Whole Sale Banking  Medium Risk        N  \n",
+       "4       Whole Sale Banking  Medium Risk        N  \n",
+       "...                    ...          ...      ...  \n",
+       "10009     Priority Banking  Medium Risk        N  \n",
+       "10010  Ultra High NetWorth  Medium Risk        Y  \n",
+       "10011          Mass Market  Medium Risk        N  \n",
+       "10012               Others     Low Risk        N  \n",
+       "10013               Others     Low Risk        N  \n",
+       "\n",
+       "[10014 rows x 9 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# sen = Scenario()\n",
+    "# sen.logic()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "150bb5ce-6be1-44fc-a606-6d375354626d",
+   "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..2f5e9af
--- /dev/null
+++ b/main.py
@@ -0,0 +1,150 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[1]:
+
+
+import pandas as pd
+
+
+# In[5]:
+
+
+from tms_data_interface import SQLQueryInterface
+seq = SQLQueryInterface(schema="transactionschema")
+
+
+# In[6]:
+
+
+seq.execute_raw("show tables")
+
+
+# In[7]:
+
+
+query = """
+    select  final.CUSTOMER_NUMBER_main as Focal_id,
+            final.Credit_transaction_amount,
+            final.Total_no_of_credit_transactions,
+            final.Debit_transaction_amount,
+            final.Total_no_of_debit_transactions,
+            final.Wash_Ratio,
+            final.SEGMENT,
+            final.RISK,
+            final.SAR_FLAG
+    from 
+    (
+        (
+            select subquery.CUSTOMER_NUMBER_1 as CUSTOMER_NUMBER_main,
+                    subquery.Credit_transaction_amount,
+                    subquery.Total_no_of_credit_transactions,
+                    case
+                         when subquery.Debit_transaction_amount is NULL then 0
+                         else Debit_transaction_amount
+                    end as Debit_transaction_amount,
+                    case
+                         when subquery.Total_no_of_debit_transactions is NULL then 0
+                         else Total_no_of_debit_transactions
+                    end as Total_no_of_debit_transactions,
+                    case
+                         when subquery.Debit_transaction_amount = 0
+                         or subquery.Debit_transaction_amount is NULL then 0
+                         else subquery.Credit_transaction_amount / subquery.Debit_transaction_amount
+                    end as Wash_Ratio
+            from 
+            (
+                (
+                    select customer_number as CUSTOMER_NUMBER_1, 
+                            sum(transaction_amount) as Credit_transaction_amount, 
+                            count(*) as Total_no_of_credit_transactions
+                    from 
+                    (
+                        select * 
+                        from {trans_data} as trans_table left join {acc_data} as acc_table
+                        on trans_table.benef_account_number = acc_table.account_number
+                    )
+                    where account_number not in ('None')
+                    group by 1
+                ) credit left join
+                (
+                    select customer_number as CUSTOMER_NUMBER_2, 
+                            sum(transaction_amount) as Debit_transaction_amount, 
+                            count(*) as Total_no_of_debit_transactions
+                    from 
+                    (
+                        select * 
+                        from {trans_data} as trans_table left join {acc_data} as acc_table
+                        on trans_table.orig_account_number = acc_table.account_number
+                    )
+                    where account_number not in ('None')
+                    group by 1
+                ) debit on credit.CUSTOMER_NUMBER_1 = debit.CUSTOMER_NUMBER_2 
+            ) subquery
+        ) main left join 
+        (
+            select subquery.CUSTOMER_NUMBER_3 as CUSTOMER_NUMBER_cust,
+                    subquery.SEGMENT,
+                    subquery.RISK,
+                    case
+                         when subquery.SAR_FLAG is NULL then 'N'
+                         else subquery.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
+            ) subquery
+        ) cust_alert on cust_alert.CUSTOMER_NUMBER_cust = main.CUSTOMER_NUMBER_main
+    ) final
+"""
+
+
+# In[8]:
+
+
+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", "Credit_transaction_amount",
+                "Total_no_of_credit_transactions",
+                "Debit_transaction_amount", "Total_no_of_debit_transactions",
+                "Wash_Ratio", "Segment", "Risk", "SAR_FLAG"]
+        df = pd.DataFrame(row_list, columns = cols)
+        return df
+
+
+# In[9]:
+
+
+# sen = Scenario()
+# sen.logic()
+
+
+# In[ ]:
+
+
+
+