Your company stores its data in Snowflake. Your stakeholders work in Excel. Getting from one to the other is something you will likely need to do more than once, so it is worth understanding your options before committing to an approach.

This guide covers four methods: the Snowflake ODBC driver, the Snowflake Excelerator Excel Add-In, Power Query via ODBC, and using Mammoth Analytics to connect, transform, and export clean data to Excel. Each suits a different situation. The comparison table near the end will help you decide.

Method 1: Snowflake ODBC Driver

ODBC (Open Database Connectivity) is a standard interface that lets applications like Excel connect to external databases using a driver. Snowflake provides its own free ODBC driver, and once it is installed and configured, Excel can query Snowflake data directly. This is the most widely used method and works on both Windows and Mac.

Before you start: check your Excel version

The single most common failure point with this method is a mismatch between the driver architecture and Excel’s architecture. You need the 32-bit driver if your Excel is 32-bit, and the 64-bit driver if your Excel is 64-bit. This applies regardless of what version of Windows you are running.

To check on Windows, open Excel and go to File > Account > About Excel. The dialog will clearly state “32-bit” or “64-bit”. Note this before downloading anything.

On Mac, go to Excel menu > About Microsoft Excel to check your version.

Windows: Installing and configuring the ODBC driver

Step 1: Download the driver

Go to Snowflake’s ODBC driver download page and download the installer that matches your Excel architecture. Run the installer and follow the prompts. Administrator privileges are typically required.

Step 2: Configure a DSN (Data Source Name)

A DSN stores your Snowflake connection details so Excel can find the database. To create one:

1. Search for “ODBC Data Sources” in the Windows search bar. You will see two versions: “ODBC Data Sources (32-bit)” and “ODBC Data Sources (64-bit)”. Open the one that matches your Excel version. This step is critical: creating a DSN in the wrong version means it will not appear in Excel.
2. Under the User DSN tab, click Add.
3. Select SnowflakeDSIIDriver from the list and click Finish.
4. In the configuration dialog, enter:
   • Data Source: A name you choose (e.g., “Snowflake_Prod”)
   • Server: Your Snowflake account identifier in the format account-identifier.snowflakecomputing.com. Do not include https://
   • Warehouse: The virtual warehouse you want to use for queries
   • Database: The database you want to query
   • Schema: Optional, but recommended if you want to narrow the connection scope
   • User: Your Snowflake username
5. Click OK. The password field accepts a value but does not store it. You will enter your password each time you connect. This is a deliberate security measure documented in Snowflake’s Windows ODBC guide.

Step 3: Connect from Excel

1. Open Excel and go to the Data tab.
2. Click Get Data > From Other Sources > From ODBC.
3. Select the DSN you created from the dropdown and click OK.
4. Excel will prompt you for your Snowflake username and password.
5. The Navigator window will appear showing available databases, schemas, and tables. Select a table and click Load to import it into a worksheet, or Transform Data to open Power Query before loading.

Mac: Installing and configuring the ODBC driver

Mac setup requires one additional component that Windows users do not need: iODBC, the ODBC driver manager for macOS.

Step 1: Install iODBC

Download iODBC from iodbc.org. Open the .dmg file, run iODBC-SDK.pkg, and follow the installation prompts. By default it installs to /Library/Application Support/iODBC/bin.

Step 2: Download and install the Snowflake ODBC driver for Mac

Download the macOS installer from Snowflake’s ODBC driver download page. Open the .dmg file, run the .pkg installer inside it, and follow the prompts. You will likely be asked for your administrator password.

Step 3: Configure a DSN via odbc.ini

On Mac, DSNs are configured by editing a plain text file rather than through a GUI. Create or edit ~/.odbc.ini (for a user DSN) and add an entry in this format:

[Snowflake]
Driver=/opt/snowflake/snowflakeodbc/lib/universal/libSnowflake.dylib
server=account-identifier.snowflakecomputing.com
warehouse=MY_WAREHOUSE
database=MY_DATABASE
schema=MY_SCHEMA
uid=my_username

Per Snowflake’s macOS ODBC documentation, the iODBC GUI administrator tool has not been tested with Snowflake and should not be used to create or manage DSNs. Edit the .ini file directly.

Step 4: Connect from Excel on Mac

The path is the same as Windows: Data > Get Data > From Other Sources > From ODBC. Select your DSN and authenticate when prompted.

Limitations of the ODBC method

• Initial setup is moderately complex, particularly on Mac
• The 32-bit/64-bit mismatch is the most common cause of failed connections on Windows
• Excel has a hard row limit of 1,048,576 rows per worksheet. If your Snowflake query returns more, you will need to filter at the query level before importing
• Data does not refresh automatically; you must reconnect and re-run the query each time you need updated data

Method 2: Snowflake Excel Add-In (Excelerator)

Snowflake Labs maintains an open-source Excel Add-In called Excelerator, available on GitHub. It is a Windows-only .xlam file that adds a Snowflake section to the Excel ribbon, letting you pull data from Snowflake without manually configuring ODBC.

Important: Excelerator is Windows-only and does not support Excel on Mac. Mac users should use Method 1 or Method 4.

Installation

1. Download the .xlam file from the Excelerator GitHub repository. There are two versions: a read-only version (SnowflakeExcelAdd-InReadOnly.xlam) and a full version that also allows writing data back to Snowflake.
2. Before installing, right-click the downloaded file, select Properties, check the Unblock checkbox, and click OK. Skipping this step will cause security warnings during installation.
3. Copy the file to your Excel Add-Ins folder: open File Explorer, paste %APPDATA%\Microsoft\AddIns into the address bar, and drop the .xlam file there.
4. In Excel, go to File > Options > Add-Ins. Set the dropdown at the bottom to Excel Add-ins and click Go. Click Browse, navigate to the file, and click OK.

After installation, a Snowflake section will appear in the Home tab ribbon.

Connecting to Snowflake

Click Connect in the ribbon and enter:

• Server URL: Your account identifier in the format account-identifier.snowflakecomputing.com
• User ID and Password, or SSO if your organization has it configured
• Role and Warehouse are optional. Your Snowflake user defaults are used if left blank

Querying data

Click Query to open a dialog where you can select a database, schema, and table. You can choose specific columns or write a custom SQL statement. Click Execute to pull the results into the active Excel worksheet.

Limitations

• Windows only, no Mac support
• Excelerator is community-maintained via GitHub, not an officially supported product
• Data is static once imported; no automatic refresh without manually re-running the query
• The SQL editor is basic compared to writing queries directly in Snowflake

Method 3: Power Query via ODBC

Power Query is built into Excel (Microsoft 365, Excel 2016, and later). It lets you connect to external data, apply light transformations visually, and load the result into a worksheet or data model. When connecting to Snowflake from Excel, Power Query uses the same ODBC driver as Method 1, so the driver must be installed and a DSN configured first.

The practical difference from Method 1 is what happens after connection. Power Query lets you filter rows, rename columns, change data types, and do basic reshaping before anything lands in the spreadsheet. For users who need light preparation before analysis, this is a genuine improvement over loading raw tables directly.

Steps

1. Complete the driver installation and DSN configuration from Method 1.
2. In Excel, go to Data > Get Data > From Other Sources > From ODBC.
3. Select your Snowflake DSN and authenticate.
4. In the Navigator dialog, select the table or view you want to work with.
5. Instead of clicking Load, click Transform Data to open the Power Query Editor.
6. Apply any filters, column renames, or reshaping steps. All changes are recorded as steps and can be edited later.
7. Click Close & Load to bring the transformed result into your worksheet.

Refreshing data

Once a Power Query connection is set up, you can refresh it from the Data tab using Refresh All. This re-runs the query against Snowflake and updates the worksheet. The Snowflake ODBC driver must be installed on any machine that performs the refresh, including any colleague you share the workbook with.

Limitations

• Requires the same ODBC driver installation as Method 1
• Refresh is manual unless you configure scheduled refresh in Excel Online via Power Automate, which requires additional Microsoft 365 licensing and setup
• Transformation capability is limited. Complex multi-table joins or large aggregations are better handled before data reaches Excel
• The 1,048,576-row worksheet limit still applies

Method 4: Mammoth Analytics

The three methods above share the same core limitation: they deliver raw Snowflake data to Excel. If that data is already in the exact shape your report needs, that is fine. In practice, it rarely is.

Most teams querying Snowflake for Excel reports need to join tables, filter rows, aggregate, clean inconsistent values, or reshape the structure before the file is usable. With ODBC or Power Query, that work happens in Excel and has to be done again manually every time someone needs a refreshed file.

Mammoth Analytics is a no-code data preparation platform that connects directly to Snowflake, lets you build a saved transformation pipeline, and exports a clean CSV or XLSX on demand or on a schedule. The Snowflake connection uses the same credentials as ODBC: Account, Warehouse, Database, Schema, Username, and Password. Nothing new needs to be configured on the Snowflake side.

How it works

Connect to Snowflake

In Mammoth, create a new dataset and select Snowflake from the connector list. Enter your account identifier, warehouse, database, schema, username, and password. Mammoth saves the connection as a Live Connection that persists across projects without re-entering credentials.

Build a transformation pipeline

Once the data is imported, you work in Mammoth’s visual pipeline interface. Transformations are applied as discrete steps: filter rows by condition, join datasets from different sources, group and aggregate, rename and reformat columns, apply conditional logic, and more. You can also write SQL directly using the SQL Query task. Everything runs without code outside of optional SQL queries.

Because the pipeline is saved, you build the logic once. Every subsequent export runs the same steps automatically against whatever data is currently in Snowflake.

Export to Excel

From the Export menu, select CSV or XLSX. The file downloads immediately. For recurring reports, Mammoth’s orchestration features let you schedule pipeline runs and file delivery daily, weekly, or monthly. The output is always current without anyone manually running the export.

When this method makes sense

This approach is worth setting up when:

• You run the same Snowflake-to-Excel report on a recurring basis
• The Snowflake data needs to be joined, filtered, or reshaped before it is useful in the report
• Multiple people need the same output and you want the preparation logic maintained in one place rather than duplicated in individual workbooks
• Manual data preparation before distributing reports is consuming significant time each week

For a simple one-off export from a single clean Snowflake table, ODBC or the Add-In is faster to get started. For anything recurring or requiring transformation, the time to build a Mammoth pipeline pays back quickly.

Mammoth offers a 7-day free trial with no credit card required.

Comparison: Which method should you use?

Troubleshooting common issues

DSN does not appear in Excel’s ODBC dropdown

Almost always a 32-bit/64-bit mismatch. Either the driver was installed for a different architecture than your Excel, or you configured the DSN in the wrong version of ODBC Data Source Administrator. Check your Excel architecture in File > Account > About Excel, uninstall the driver, download the correct version from Snowflake’s download page, and recreate the DSN in the ODBC administrator version that matches your Excel.

“Account not found” or connection timeout

Your server value must be in the format account-identifier.snowflakecomputing.com. Do not include https://. The full Snowflake web login URL that contains app.snowflake.com is not the account identifier and will not work in ODBC connection fields.

Warehouse suspended or unavailable

Snowflake automatically suspends idle warehouses to reduce compute costs. If your connection times out with a warehouse error, log into Snowflake and verify the warehouse is running and that your user role has USAGE privilege on it. Your Snowflake administrator can adjust auto-suspend settings or grant the appropriate role.

“Login failed” authentication error

Verify your username and password against your Snowflake account. If your organization uses SSO or multi-factor authentication, standard username/password ODBC authentication may not be permitted for your account. Check with your Snowflake administrator about the correct authentication method.

Row limit hit in Excel

Excel loads a maximum of 1,048,576 rows into a single worksheet. If your Snowflake query returns more, the import will be truncated without an error. Add a WHERE clause or date range filter to your query before importing, or use Power Query’s filtering steps to reduce the result set before it loads.

Frequently asked questions

Can I connect Snowflake to Excel on a Mac?

Yes, using the ODBC method. The Snowflake ODBC driver has a macOS installer, and DSNs are configured by editing the odbc.ini file as described in Method 1. The Excelerator Add-In does not support Mac. Mammoth Analytics is browser-based and works on any operating system.

Is there a free Snowflake Excel connector?

The Snowflake ODBC driver is free, available at Snowflake’s developer downloads. The Excelerator Add-In is free and open-source on GitHub. Power Query is included in Excel at no extra cost. Mammoth Analytics offers a 7-day free trial.

Does refreshing Snowflake data in Excel require the ODBC driver on every machine?

Yes. For both the ODBC method and Power Query via ODBC, the Snowflake driver must be installed on any machine where a user refreshes the connection. Sharing the workbook with a colleague who does not have the driver installed means they cannot refresh the data without installing the driver themselves first.

What is the row limit for Snowflake data in Excel?

Excel’s worksheet row limit is 1,048,576 rows, regardless of which connection method you use. For larger datasets, filter at the Snowflake query level or use Excel’s Data Model via Power Pivot, which can handle larger row counts than a standard worksheet. With Mammoth, transformation and filtering happen before export, so only the rows the report actually needs end up in the downloaded file.

How can I get Snowflake data into Excel automatically on a schedule?

None of the native Excel connection methods offer automated scheduling without additional tools. Power Query can be combined with Power Automate and Excel Online for scheduled refresh, but this requires additional Microsoft 365 configuration. Mammoth’s orchestration features handle scheduling natively. The pipeline runs and the file is delivered at a defined interval without additional infrastructure. You can explore how this works with a free trial at mammoth.io/signup.