diff --git a/README.md b/README.md
index d9cd2b3..c813ec2 100644
--- a/README.md
+++ b/README.md
@@ -8,7 +8,7 @@ UniverSQL relies on Snowflake and Polaris for access control and data catalog so
 > Any SQL client that supports Snowflake, also supports UniverSQL as we implement Snowflake's API to support compatibility. If you run into any issue using an app or client, feel free to [create a discussion](https://github.com/buremba/universql/discussions/categories/quality-testing). 
 
 
-[![Demo](./resources/demo.gif)](https://www.youtube.com/watch?v=s1fpSEE-pAc)
+[![Demo](./resources/cli_demo.png)](https://www.youtube.com/watch?v=s1fpSEE-pAc)
 
 **[Watch on YouTube](https://www.youtube.com/watch?v=s1fpSEE-pAc)**
 
diff --git a/resources/cli_demo.png b/resources/cli_demo.png
new file mode 100644
index 0000000..bcfb7c2
Binary files /dev/null and b/resources/cli_demo.png differ
diff --git a/testing.ipynb b/testing.ipynb
index 5d7398b..92c34ab 100644
--- a/testing.ipynb
+++ b/testing.ipynb
@@ -2,12 +2,12 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 1,
    "id": "initial_id",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2024-08-25T02:20:31.964329Z",
-     "start_time": "2024-08-25T02:20:30.625246Z"
+     "end_time": "2024-08-28T00:18:33.458129Z",
+     "start_time": "2024-08-28T00:18:30.285012Z"
     }
    },
    "outputs": [],
@@ -30,10 +30,7 @@
      "end_time": "2024-08-23T14:30:35.029029Z",
      "start_time": "2024-08-23T14:30:34.783445Z"
     },
-    "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
-    }
+    "collapsed": false
    },
    "outputs": [
     {
@@ -251,95 +248,33 @@
     }
    ],
    "source": [
-    "con.cursor().execute(\"show tables in tpch_sf1\").fetch_pandas_all()"
+    "con.cursor().execute(\"select C_MKTSEGMENT, count(*) from my_iceberg_jinjat.tpch_sf1.dynamic_iceberg_table_customer group by all\").fetch_pandas_all()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 2,
    "id": "d01f1e0b-d4b7-4b16-b1a8-adf73b874dde",
    "metadata": {
-    "ExecuteTime": {
-     "end_time": "2024-08-23T14:34:49.413Z",
-     "start_time": "2024-08-23T14:34:49.012550Z"
-    },
     "collapsed": false,
-    "jupyter": {
-     "outputs_hidden": false
+    "ExecuteTime": {
+     "end_time": "2024-08-28T00:18:39.392757Z",
+     "start_time": "2024-08-28T00:18:38.346465Z"
     }
    },
    "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>C_MKTSEGMENT</th>\n",
-       "      <th>count_star()</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>MACHINERY</td>\n",
-       "      <td>119796</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>AUTOMOBILE</td>\n",
-       "      <td>119008</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>FURNITURE</td>\n",
-       "      <td>119872</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>HOUSEHOLD</td>\n",
-       "      <td>120756</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>BUILDING</td>\n",
-       "      <td>120568</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "  C_MKTSEGMENT  count_star()\n",
-       "0    MACHINERY        119796\n",
-       "1   AUTOMOBILE        119008\n",
-       "2    FURNITURE        119872\n",
-       "3    HOUSEHOLD        120756\n",
-       "4     BUILDING        120568"
-      ]
+      "text/plain": "  C_MKTSEGMENT  count_star()\n0     BUILDING        120568\n1   AUTOMOBILE        119008\n2    FURNITURE        119872\n3    MACHINERY        119796\n4    HOUSEHOLD        120756",
+      "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>C_MKTSEGMENT</th>\n      <th>count_star()</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>BUILDING</td>\n      <td>120568</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>AUTOMOBILE</td>\n      <td>119008</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>FURNITURE</td>\n      <td>119872</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>MACHINERY</td>\n      <td>119796</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>HOUSEHOLD</td>\n      <td>120756</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
      },
-     "execution_count": 26,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "con.cursor().execute(\"select C_MKTSEGMENT, count(*) from my_iceberg_jinjat.tpch_sf1.dynamic_iceberg_table_customer group by all\").fetch_pandas_all()"
+    "con.cursor().execute(\"show tables in tpch_sf1\").fetch_pandas_all()"
    ]
   },
   {