Create a Dataset Using Excel

This guide walks you through creating a dataset in AIV using Excel files. Excel spreadsheets are widely used for tabular data, and AIV lets you use them directly as dataset sources.

What You’ll Learn

What an Excel file is and when to use it
Single-sheet vs multiple-sheet Excel files—when to use which, and when to show which example
How to prepare and upload your Excel file
Three ways to create a dataset: simple selection, custom query, or with parameters

What is Excel?

Microsoft Excel is a spreadsheet application that stores and organizes data in a table format. Excel files (.xlsx, .xls) are commonly used for reports, lists, and structured data that you can import into AIV.

Characteristic	Description
Format	Binary (xlsx) or legacy (xls)
Structure	Worksheets with rows and columns
Use case	Reports, lists, data exchange

Single sheet vs multiple sheets

Excel files can have one worksheet or several worksheets (tabs). How you create a dataset depends on which you have.

Scenario	When to use	Example to show
Single sheet	Your Excel file has only one worksheet, or you care only about one tab. Use this when the file is one table (e.g. a list of marathon results).	Use a single-sheet example such as `marathon.xlsx` when you want to keep steps simple and focus on the three methods (Simple, Custom SQL, Parameters) without sheet selection.
Multiple sheets	Your Excel file has more than one worksheet and you need to choose a sheet, combine sheets, or reference a specific tab in a query.	Use a multiple-sheet example when you need to document how to pick a sheet from the file, or how to write SQL that references different sheets (e.g. `SELECT * FROM [Sheet1$]` vs `[Sales$]`).

In this guide: The steps use a single-sheet example (marathon.xlsx) so you can follow one clear path. If your file has multiple sheets, after selecting the file you will also choose which sheet to use (or write a query that targets a specific sheet); the rest of the flow (Simple, Custom SQL, Parameters) is the same.

Prerequisites

Before you begin, complete these steps:

Download the sample file: excel.zip
Extract the zip archive
Upload marathon.xlsx into AIV

Need help uploading? See the Upload guide for instructions.

Steps to Create a Dataset Using Excel

Complete Step 1 (Navigate to the Dataset Section) and Step 2 (Create a New Dataset) from the Create Dataset guide, then choose one of the three methods below.

Method	Best for
Method 1: Simple	Loading all Excel data with no changes
Method 2: Custom SQL Query	Filtering, selecting columns, or transforming data
Method 3: With Parameters	Letting users filter data at runtime (e.g., in dashboards)

Method 1: Simple — Select File and Use Default Data

Use this method when you want to load all data from your Excel file without filtering or custom queries.

Step 1: Select Excel as the Data Source

Choose Excel Files as the data source type.

Step 2: Connection Selection

For details on file selection and tab options, see Connection Selection for Excel, CSV, and JSON.

If your Excel file has a single sheet:

Click Select Existing Files.
Search for your Excel file (for example, marathon.xlsx).
Select the file from the list. With one sheet, the system uses that sheet by default.
Open the Output Columns tab to review column names and data types.
Open the Preview Results tab to verify the data.

If your Excel file has multiple sheets:

Click Select Existing Files.
Search for your Excel file and select it from the list.
Choose the sheet (worksheet) you want to use from the file—e.g. Sheet1, Sales, Summary. The dataset will use only the selected sheet.
Open the Output Columns tab to review column names and data types for that sheet.
Open the Preview Results tab to verify the data.

Select Excel File

Output Columns

Step 3: Save Dataset

Click Save.
In the Save Dataset dialog, optionally rename the dataset and select the destination folder.
Click Save Dataset to confirm.

Step 4: View Your Dataset

Go to the Dataset Grid view.
Search for your dataset by name.
Your dataset is now available for use in dashboards, reports, and visualizations.