I am an AI specialist, so I'm going to help you with this problem. You are currently working on a webpage for a website where we want to create a heading that contains certain information about the page and its functionality, while also incorporating elements of marketing research into your design. This is a high-concept exercise in web development which requires deep understanding of how to combine different types of data together to achieve optimal results. In order for this project I need you to create an SQL database query that can help me collect data on a large number of records, specifically the "Sales" table from our company' cuo01-2019 annual financial report. Our system has already been set up and we are looking for more ways to improve it. We have collected 3 million rows of sales transactions over the years 2008 - 2019, with each row representing a single transaction and containing columns "ProductName", "seller_name" (the seller), "product_id"(a unique identifier for a particular product), "order_total", "date", and more. I want you to help me write an SQL query that can find all the sales data from this table, but only select the transactions which took place in the month of March 2019. The output should be in ascending order by "ProductName". Write a python code that can do this, and also implement error handling with relevant error messages if there is no such sale in the given period.