> For the complete documentation index, see [llms.txt](https://docs.coherent.global/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coherent.global/getting-started-in-5-minutes.md).
# Get started in 5 minutes
This guide will demonstrate how easy it is to convert an Excel file to code and have a working API ready that is ready for integration! We will use a basic example to create a volume of a cone API using Spark. You can extend this example to the most complex Excel spreadsheets in the same way!
## Map inputs and outputs in Excel
Spark uses [Named Ranges](https://support.microsoft.com/en-us/office/define-and-use-names-in-formulas-4d0f13ac-53b7-422e-afd2-abd7ff379c64) to define the inputs (radius, height) and outputs (volume) from this calculation.
1. Open Excel and setup the formulas for the volume of a cone.
2. Use the Name Box to map `Xinput_r` and `Xinput_h` as inputs into the volume calculation. Spark reads the prefix `Xinput_` and identifies these Named Ranges are inputs into the calculation.
3. Use the Name Box to map `Xoutput_V` as an output of the volume calculation. Spark reads the prefix `Xoutput_` and identifies this Named Range as an output of the calculation. Spark is able to automatically process the formulas in the Excel workbook!
4. Open the *Name Manager* by clicking the **Formula** tab in the Ribbon and choosing **Name Manager**. In total, there should be 3 Named Ranges, `Xinput_r`, `Xinput_h`, `Xoutput_V`.
5. Save the file or alternatively use the pre-prepared file for the next step.
{% file src="/files/WEwnX0YLrryoD4GFrQnf" %}
## Create a folder
The first screen after logging into Spark is the [Home](/navigation/home.md) screen. On this screen Folders can be created to organize the different Spark Services (converted Excel files).
1. Create a folder to store this Excel file.
2. Enter a name for this folder.
3. Choose a Category which relates to the types of Excel files that will be uploaded to this folder.
4. Provide a description of this folder.
5. As an optional step, a Cover Image can be added as well.
6. Click **Create**.
7. The [Folder overview](/navigation/folder-overview.md) screen will be displayed.
## Add a service
In Spark, a service is created when an Excel file is converted to code and there is a corresponding API created to execute the convert code.
1. From the [Folder overview](/navigation/folder-overview.md) screen, click on **New service** to open the upload modal.
2. Click on **Browse** to select a file, or drag and drop your Excel file inside the modal to upload.
3. Enter an alternate *Service name* to refer to this file using a different name in Spark.
4. A *Version label* can make it easier to differentiate multiple service versions later.
5. Once the conversion is complete, click on **Publish** to complete the "Excel-to-code" conversion and API generation! The logic in the Excel spreadsheet is now in a Spark service!
6. You will be taken to the [API Tester](/navigation/api-tester.md) to test the converted code
## Test the converted code and execute the API
The [API Tester](/navigation/api-tester.md) can be used to test the converted code and the [Execute API (v3)](/spark-apis/execute-api/execute-api-v3.md) which performs the Spark calculations.
1. On the left API request panel, the `height` and `radius` are identified as inputs from the mapping done earlier.
2. Enter different values for the `height` and `radius` of the cone.
3. Click **Submit** to submit an API request.
4. On the right API request panel, the resulting `Volume` of the cone will be returned!
5. The *JSON view* and *Raw view* provides information useful for developers integrating to Spark's automatically generated APIs.
## Explore more features!
* For business users, there is a further explanation of the Excel Spark mappings beyond `Xinput` and `Xoutput` in [How to: Map inputs and outputs](/build-spark-services/map-inputs-and-outputs.md).
* For Administrators, read how to setup your tenant in [Tenant administration](/tenant-administration.md) and [Identity and Access Management](/identity-and-access-management/recommendations.md).
* For Developers, learn more about:
* Automatically generated calculation APIs in [Execute API](/spark-apis/execute-api.md).
* [Authorization - Bearer token](/spark-apis/authorization-bearer-token.md).
* [Authorization - API keys](/spark-apis/authorization-api-keys.md).