diff --git a/docs/modules/chains/examples/sqlite.ipynb b/docs/modules/chains/examples/sqlite.ipynb
index 548ca4c6..aaea8fbf 100644
--- a/docs/modules/chains/examples/sqlite.ipynb
+++ b/docs/modules/chains/examples/sqlite.ipynb
@@ -56,6 +56,15 @@
     "llm = OpenAI(temperature=0)"
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "3d1e692e",
+   "metadata": {},
+   "source": [
+    "**NOTE:** For data-sensitive projects, you can specify `return_direct=True` in the `SQLDatabaseChain` initialization to directly return the output of the SQL query without any additional formatting. This prevents the LLM from seeing any contents within the database. Note, however, the LLM still has access to the database scheme (i.e. dialect, table and key names) by default."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
diff --git a/langchain/chains/sql_database/prompt.py b/langchain/chains/sql_database/prompt.py
index 253b619c..2b2a97cf 100644
--- a/langchain/chains/sql_database/prompt.py
+++ b/langchain/chains/sql_database/prompt.py
@@ -26,7 +26,7 @@ PROMPT = PromptTemplate(
     template=_DEFAULT_TEMPLATE,
 )
 
-_DECIDER_TEMPLATE = """Given the below input question and list of potential tables, output a comma separated list of the table names that may be neccessary to answer this question.
+_DECIDER_TEMPLATE = """Given the below input question and list of potential tables, output a comma separated list of the table names that may be necessary to answer this question.
 
 Question: {query}