Last Updated: May 10, 2022
SQL Datasets are used for large scale data transformations or when you need to combine the data from different data sources, say an Oracle table, Jiffy Table, and CSV data. SQL Datasets are created by using SQL queries.
The following Nodes/Functions are used in Tasks to perform various actions with data in the SQL Dataset.
Consider a Sales Data Automation HyperApp, where the ProductSales reports are received every month. An SQL Dataset is created with a query to combine sales reports of different products for the month. A task is created to upload the monthly ProductSales report, combine it with the previous month's report, and get the details of products that are consistently on the top five list.
- Use the Upload CSV node to upload and publish the CSV file for ProductSales data for the month.
- Use the Dataset Refresh node to refresh the SQL Dataset and update with the latest sales reports. The data of the current month is combined with the previous data when the Join Query is executed.
- Use the Dataset node to filter and get the details of products that are at the top five list at least six times a year. A query to filter the top five products is executed.
- Use the Excel node to store the data in an Excel spreadsheet.