Data Prep (Projects)
Last updated
Was this helpful?
Last updated
Was this helpful?
Data Prep is a tool to prepare your data for applications quickly. It allows you to explore and transform data with built-in SQL actions, then automate the pipeline for your data apps
Data Prep is a tool to prepare your data for applications quickly. It allows you to explore and transform data with built-in SQL actions, then automate the pipeline for your data apps. A project is used to manage multiple tables, perform actions, and collaborate with your teammates.
In a project, you do not have to worry about overwriting or altering the original database that you have imported. You may perform whatever action you like and be able to go back in action.
Within the project, you may create many “table tabs”. These tabs are sourced from your database so that you may edit multiple tables all in once. Though they may look like a tab from your internet browser, there is a data pipeline behind each table tab. It means that you must always apply actions in sequence, and make changes to each action logically. For example, you cannot merge a table that is not open in a project or edit a filter that you have applied several steps earlier.
A project also works as a foundation for other projects on Acho Studio such as Visual Panel. When you have applied a series of actions on a project, that will produce a table you can work on further on Visual Panel.
In order to create Data Prep Project you need to have at least one Resource in your organization.
Data Prepcan be conveniently accessed from the sidebar menu. To initiate the interface, simply click on the "Data Prep" in the sidebar. Upon entering this interface, you will see a layout listing all the project you have. If there is no project in the organization, you will be led to create a Data Prep Project from resources.
Create a Data Prep Project
Create a data preparation project (Data Prep) in Acho Studio
Apply an action
Explore, clean and transform data with built-in SQL actions, such as sort, filter, join, deduplicate and flatten.
Pipeline
Create and visualize automated process to transform your data.
