A. Create two separate charts: a pie chart for product category sales and a table for regional sales. Use the same filter on the dashboard for region, and manually enter the date range in the SQL query for the table chart.

B. Create a single Snowsight dashboard with two charts: a pie chart showing total sales by product category using the query 'SELECT PRODUCT_CATEGORY, SUM(SALES AMOUNT) FROM SALES DATA WHERE REGION = $REGION GROUP BY PRODUCT_CATEGORY, and a table showing regional sales using the query 'SELECT REGION, FROM SALES_DATA WHERE ORDER_DATE BETWEEN $START_DATE AND $END_DATE AND REGION = $REGION GROUP BY REGION'. Define three dashboard variables: 'REGION' (Dropdown), 'START DATE (Date), and 'END DATE (Date).

C. Create a single Snowsight dashboard with a Python chart for product category sales, querying data using Snowflake Connector, and a table showing regional sales using SQL query. No dashboard variables are needed, as the Python script handles all filtering.

D. Create two separate dashboards: one for the pie chart and another for the table. Use a global session variable to store the selected region and date range, and access it in the SQL queries for both dashboards.

E. Create a view with all calculations of the total sale amount, grouping by product category and region. Then create the dashboard with charts based off of this view. This will allow for easier modification if the business requirements change.