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ADA Overview

What is ADA?

ADA stands for Audit Data Assistant, a Windows application developed by Audit Data Analytics, LLC. ADA features tools for analyzing audit data and is offered at no cost via open source licensing.

Installation

After downloading the ADA-Setup.msi file from the web site and saving it to a convenient place on your computer, double-click it to run the setup.

Project Folder

When you run ADA the first time, you will be asked to specify a working project folder. Creating a folder for ADA documents under My Documents or Documents in your user folder is recommended, but you can choose to create one anywhere. The project folder is key to ADA’s operation. Your project folder is where you keep the files you’re working with for a particular project or audit. The current project folder is indicated at the bottom left of the ADA Project Viewer window.

File Explorer

ADA’s File Explorer is on the left side of the Project Viewer window. It lists all data files in the current project folder in tree form so you can see parent/child relationships between the data files. From here, you can open a file in a tab on the right side of the Project Viewer by double-clicking the file or by right-clicking the file and selecting Open. You can also right click and perform Rename and Delete operations. To resize the File Explorer, place your mouse pointer in the blank space between the File Explorer and the Data Viewer Tabs and then click and drag the double arrow guide.

Data Viewer Tabs

When you open a file for viewing in ADA, it opens a grid view in a tab in the Data Viewer area on the right side of the Project Viewer window. These tabs allow you to open multiple data files at once and switch between them easily. You can also easily move these tabs around to order your data files however you wish.

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ADA Help Contents

ADA Overview

How to Import Data with ADA

How to Quick Export Data with ADA

How to Manage Columns with ADA

How to Write Criteria with ADA

How to Filter Data with ADA

How to Join Data with ADA

How to Detect Duplicates with ADA

How to Summarize Data with ADA

How to Append Data with ADA

How to Sort Data with ADA

How to Plan an Attribute Sample with ADA

How to Perform Error Assurance with ADA

How to Evaluate an Attribute Sample with ADA

How to Plan a Variable Sample with ADA

How to Evaluate a Variable Sample with ADA

How to Plan a MUS Sample with ADA

How to Evaluate a MUS Sample with ADA

How to Random Sample with ADA

 

 

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