Compare Export Data with Power BI Models

Purpose/Overview

In this article, you will learn how to use the Exports vs. Power BI Data Dictionary to compare ticket data available in Pick-your-own Exports with columns and measures available in the Power BI live and historical ticket models. This reference can help you select appropriate data elements, understand differences between reporting sources, and investigate results that do not appear to match. 

Navigation Path:

Click here to download the Data Dictionary.

Things to Know:

• The data dictionary is a comparison reference. Not every export field has a direct equivalent in both Power BI models.
• N/A indicates that the dictionary does not identify a direct mapping for that source or model.
• A column is a field used to filter, group, label, or display ticket information.
• A measure is a calculated result, such as a ticket count, percentage, average, or elapsed-time value.
• Power BI measures are evaluated within the filters and context of a report. Therefore, a measure may not match a ticket-level export field one-to-one.
• Before using an element in a report, review both its Data Description and Usage Notes.

Key Benefits/Use Cases:

• Find the Power BI element that most closely corresponds to an export field.
• Identify fields that are available only in an export or only in a Power BI model.
• Compare element availability between the live and historical ticket models.
• Determine whether an element is a column or a measure before adding it to a report.
• Use documented definitions and usage guidance to support report development and validation.

How It Works:

1. Choose a starting point. If you know the export field, locate it in the Pick-your-own Export Field Name column. If you are starting in Power BI, filter by the applicable table and element name.
2. Review the live and historical mappings. Compare the Live Tickets and Historical Tickets columns to see whether the element is available in either model and whether its name differs between models.
3. Check the element type. Use BI Element Type to determine whether the item is a column or a measure. Columns generally represent ticket attributes, while measures return calculated results.
4. Read the description. Use Data Description to confirm what the field or measure represents.
5. Review the usage notes. Use Usage Notes to identify reporting context, calculation behavior, limitations, or common use cases.
6. Interpret N/A values. When a cell contains N/A, the dictionary does not identify a direct mapping in that location. Review related elements to determine whether another field or measure supports your reporting need.

Data Dictionary Column Guide

FAQ/Troubleshooting:

Q: Why does an export field show N/A in Power BI?

A: The dictionary does not identify a direct mapping for that model. The data may be available only in the export, represented by a different model element, or not included in that model.

Q: Why does a Power BI result differ from an export?

A: Confirm that both sources use the same ticket population, date range, and filters. Also check whether the Power BI element is a measure. Measures calculate results within the current report context, while export fields generally provide ticket-level values.

Q: Should I use a column or a measure?

A: Use a column when you need to filter, group, label, or display an attribute. Use a measure when you need a calculated result, such as a count, percentage, average, or duration.

Q: How can I find Power BI-only elements?

A: Filter Pick-your-own Export Field Name to N/A, and then review the live and historical model columns to see where each element is available.

Q: How can I find export-only fields?

A: Filter the Power BI table and element columns to N/A, and then review the export field name and description.

Q: What should I do if similar elements have different names?

A: Review the Data Description, BI Element, and Usage Notes rather than relying on the name alone. These columns provide the context needed to determine whether the elements support the same reporting purpose.

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