Datarails Overview: From Data Inputs to First Outputs (Exercise)

Introduction

This exercise aims to help you understand how Datarails works by walking through a simple, end-to-end workflow. You will follow the data as it moves from inputs, through the Data Mapper, and finally to the outputs.

Data Inputs: Data is brought into the system through manual uploads or integrations. At this stage, the data is stored but not yet structured for reporting.

Data Mapping: The data is mapped into tables (databases), where it is structured, transformed, and enriched using custom fields and lookups.

Dashboard Readiness: Once mapped, the data becomes dashboard-ready and can be used to build widgets and dashboards.

Function & Report Creation: Functions connect the databased data to the Excel Add-in or Report Builder, enabling dynamic, formula-driven reporting.

By completing this exercise, you’ll gain a clear understanding of how the database flows within Datarails and how each stage contributes to the overall process. This foundational knowledge is essential for building more advanced databases and for effectively troubleshooting issues as they arise in the future. 

Estimated completion time: 20–30 minutes

Important

For the purpose of this exercise, we recommend completing it in your practice environment (please register here to request access, it may take 1-2 business days), or in your actual environment but mapped to a separate table so it doesn't affect your implementation or current processes. 

Instructions on how to map data in a separate table will be provided throughout the exercise.

Section 1: Inputs 

We get the data in the system either by manual uploads or through an integration. In this exercise, we’ll be doing a manual upload. If the data is coming from an integration, your Datarails Integration Specialist will help you set that up. 

Uploading or receiving data into the environment through an integration doesn’t mean the data is "databased”; it’s just stored in the system.

Exercise 1: Upload Inputs

For this exercise, you’ll create a new filebox and upload a file into your Workspace. 

The file you’ll need to upload can be found here.

Video and step-by-step instructions

1. Navigate to Actuals Section

Click the Actuals folder to access the relevant data input area. In this exercise, we already have a filebox called "GL" within the Actuals folder. For more information about creating fileboxes check out this article on Filebox Overview.

Navigate to Actuals Section

2. Open Upload Interface

Click the Upload button to begin the process of submitting your input files.

Open Upload Interface

3. Select the relevant period

Click on the month to specify the reporting period for your data upload. Select the appropriate month from the designated period for your upload. Click the Upload button to confirm and proceed with submitting your inputs.

Choose the relevant Month

4. Complete Upload Process

Click here to finalize the upload and ensure your data is successfully submitted.


Section 2: Data Mapper

Now that the data is stored in the environment, it’s time to get it into the database. In Datarails, we do that with the Data mapper. This process includes not only databasing the needed information, but also manipulating, cleaning, and transforming the data with custom fields/lookups.

For this exercise, you’ll need to map the headers and create two custom columns:

  • Reporting Month: The goal of this custom column is to transform dates to end-of-month dates, so we can aggregate them monthly. Recommended formula = EOMONTH([Reference Date])
  • Amount: Our data has two columns with amounts, one for debits and one for credits. We want to centralize the amounts into one column so we can use that field when creating outputs. Recommended formula = [Debit (USD)] - [Credit (USD)] 

Exercise 2: Data Mapper

Video and step-by-step instructions

  1. Open Data mapper Feature

Click here to access the main menu where you can find the Data mapper feature.

Open Datamapper Feature

2. Select Data mapper Option

Click "Data mapper" to open the data mapping interface within Datarails.

Select Datamapper Option

3. Choose a Table to map the data

Choose the appropriate table (database) from the dropdown menu to indicate where you are mapping the data. In this example, we select the "Financials" table. For the purpose of this exercise, we recommend choosing a table where you haven't mapped any other data yet, to avoid mixing data. To create a new table, click on "New +", give it a name, and then select it.

Choose Financials Category

4. Confirm Selection

Click "Select" to confirm your chosen Table and Mapper Name for the mapping process.

Confirm Selection

5. Choose Flat Table Format

Click "Flat table" to specify the data structure format for your mapping.

Choose Flat Table Format

6. Add Headers to Table

Click "+ Add headers" to begin adding column headers to your data table.

Add Headers to Table

7. Complete Header Addition

Click "Done" to finalize the addition of headers to your data table.

Complete Header Addition

8. Add Custom Column

Click "+ Add custom column" to create a new column tailored to your specific data needs.

Add Custom Column

9. Open Type Selection

Click "Type..." to enter the name of your custom column.

Open Type Selection

10. Initiate Function Search

Click "Search" to find functions that can be applied to your custom column. Choose the EOMONTH function.

Initiate Function Search

11. Search for Reference Date

Click "Search" again to find the Reference Date field for your function.

Search for Reference Date

12. Apply Custom Column Settings

In this example, we're creating a custom column to display the End-Of-Month date for the relevant period. Click "Apply" to save your custom column configuration with the chosen function. Your formula should look like this: EOMONTH([Reference Date]).

Apply Custom Column Settings

13. Publish and Scan Data Mapping

Click "Publish & scan" to finalize your data mapping and initiate a scan for validation.

Publish and Scan Data Mapping

14. Confirm Publish Action

Click "OK" to confirm and complete the publishing and scanning process of your data map.


Section 3: Lookup Configuration

In Datarails, lookups provide structure, logic, and hierarchy to the data, acting as data mapping files that enhance your main database by connecting it with additional fields, groupings, or categories from another data source.

For example, a General Ledger input file can connect to a Chart of Accounts lookup to add more data layers.

Similar to an Excel Lookup, there must be at least one common key in the Lookup file and in the database (in the files you already mapped). For example, for the General Ledger to connect to a CoA, our keys would be “Account ID” and “Currency” (or Account ID and Entity, etc.).

Important considerations:

  • The name of the key must match the name of the key field in the Data mapper (eg, Account ID vs Account ID number, won't work)
  • In the lookup file, the key(s) must be on the left, starting in cell A1. Eg, if my keys are “Account ID” and “Currency”, Account ID must be in cell A1 and Currency in cell B1. All the groupings, mappings, or hierarchies that we are trying to bring to the database would be to the right of those columns.
  • The spelling of values in the lookup file vs the spelling of values in the database must also match for the system to find a match.

Exercise 3: Lookup Configuration

Files

For this exercise, we will create a Lookup filebox under the Configuration section in the left side panel, and set up the LUT configuration.

The file you’ll need to upload can be found here.

Video and step-by-step instructions

1. Access Configuration Menu

Click the Configuration menu to begin setting up your lookup file.

Access Configuration Menu

2. Open Lookups Section

Click the Lookups option to access lookup file management features.

Open Lookups Section

3. Initiate New Lookup Creation

Click the New + button to start creating a new lookup file.

Initiate New Lookup Creation

4. Select New Lookups Option

Click New Lookups to proceed with adding a new lookup file.

Select New Lookups Option

5. Enter Lookup File Name

Enter your lookup file name to identify it within the system.

Enter Lookup File Name

6. Upload Lookup File

Click the upload area to drag and drop your lookup file or browse to select it from your device.

Upload Lookup File

7. Create Lookup File

Click the Create button to finalize the creation of your lookup file.

Create Lookup File

8. Configure Source and Target Tables

Select the Target Table, Sheet Name and Key Length to configure your Lookup.

Configure Source and Target Tables

9. Save Lookup Configuration

Click the Save button to store your lookup file settings.

Save Lookup Configuration

10. Open Data Mapper

Navigate back to the Workspace > Actuals folder and click the 3 dots next to the GL filebox. Click Data mapper to review how your lookup data maps to financial reports.

Open Data Mapper

11. Review Data mapper

Notice a binocular icon will appear next to the key fields. Hover over it to see more details about the lookup.

Review Datamapper

12. Scroll until seeing green columns

Scroll through the Data mapper to see the green columns brought through the lookup configuration.

Scroll until seeing green columns


Exercise 3.1: Additional Custom Column

For this exercise, we will create an additional custom column using some of the fields we have added with the Lookup configuration. 

The goal is to modify the “Amount” custom column to multiply by the field “Sign”. This way, we’ll have our amounts in absolute values in the database.

Video and step-by-step instructions

1. Click Custom Column 3 dots

Click here to access the custom column section where you can make edits.

Click Custom Column 3 dots

2. Select Edit Option

Click "Edit" to begin modifying the selected custom column.

Select Edit Option

3. Edit the formula

Enter an asterisk (*) after the existing formula and add the [Sign] field right after it. We want to multiply the amounts by the Sign field. 

Edit the formula

4. Apply Changes

Your formula should look like this: [Debit (USD)] - [Credit (USD)] * [Sign]. Click "Apply" to save the changes made to the custom column settings. 

Apply Changes

5. Publish And Scan Column

Click "Publish & scan" to finalize and apply the custom column edits across the dataset.


Section 4: Creating Outputs

Once the data is mapped, it is dashboard-ready! You can now build as many widgets and dashboards as needed with this data. Refer to the dashboards training for more details.

In order to use the data to user reports, the next step is to create a function. A function links the data that we have on the database, with Datarails Formulas in Excel or using the Report builder in the Datarails environment. Once a function is created, you can build as many reports as needed. 

Happy building!


Exercise 4: Creating Outputs


In this exercise, you’ll create a function and create your first output using the Report Builder.

Video and step-by-step instructions

Create a function

1. Open Excel Add-In

Click the Excel Add-in on the left side panel.

Open Excel Add-In

2. Access Functions Section

Click Functions to view and manage available functions.

Access Functions Section

3. Initiate New Function Creation

Click here to start creating a new function.

Initiate New Function Creation

4. Enter Function Name

Enter your function name.

Enter Function Name

5. Select the table

Select the table from which you would like this function to retrieve information.

Select the table

6. Open Search Field

Search and drag the relevant numeric field for example, 'Amount', to the Values section.

Open Search Field

7. Default Aggregation Field

From the dropdown, select a default aggregation field (e.g., 'Reporting Month') to structure your data

Default Aggregation Field

8. Save the Function

Click Save to finalize and store your new function.

Save the Function

Create an output using the Report Builder

Video and step-by-step instructions

1. Open Report Builder

Click the Report Builder to start creating a new report.

Open Report Builder

2. Start New Report

Click New report to begin building your report. Enter your report name to identify it clearly.

Start New Report

3. Select the relevant Function

Select the dropdown menu and choose the appropriate function you wish to use (e.g., Value).

Select the relevant Function

4. Open Search Field

Click the Search field to find specific data fields. Drag them into the relevant categories (Columns, Rows, Filters).

Open Search Field

5. Add filters as needed

Click the filter icon next to each field to access the filter selection menu.

Add filters as needed

6. Filter by P&L items

In this example, we are filtering by Expenses and Revenue

Filter by P&L items

7. Open Additional Options

Click the indicated area to access sorting options.

Open Additional Options

8. Open Sorting Options

Choose your preferred sorting method. In this exercise, switch it from "A to Z" to "Z to A" so Revenue shows on top of Expenses.

Open Sorting Options

9. Calculated Values

Click on the calculator icon next to each field to create custom columns or rows

Calculated Values

10. Enter Custom Row Name

Enter the name for your custom row to identify it clearly. In this exercise, we are using "Gross Profit".

Enter Custom Row Name

11. Enter the formula

Click on the white box to start typing your formula. In this example we are using [Revenue]-[Expenses]

 

Enter the formula

12. Select the position

Click Position to select where to add the custom row. In this exercise, we are choosing below "#Expenses".

 

Select the position

13. Save Custom Row

Click Save to store your custom row changes.

Save Custom Row

14. Save Final Report

Click Save to finalize and save your complete report.

Save Final Report

 








 




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