In this Quick Start Guide (QSG), you'll explore how to use Nexadata’s powerful tools to connect, transform, and analyze a sample beverage sales data set. The goal is to understand how cola and non-cola products are performing across different states. Throughout this guide, you will learn how to create a data connection, build a data pipeline, set up mapping groups, and run the pipeline to view the results. You will also experience using both Nexadata’s natural language interface and advanced mode to process the data. While this guide covers a simple example, Nexadata has the capacity to handle much larger datasets, connect to various data sources, and apply complex transformations to help you manage your data more efficiently.
Step #1 - Create a Connection
From the Nexadata home screen, select Create a Connection
Provide a unique Name for the data connection.
Select the Connection Type from the list of available options.
Enter the required connection details based on the selected option. In the example below, we are using Nexadata File Manager, which does not require credentials.
When complete, Submit the connection for validation.
👍 Select the Setup → Connections to return to the editing interface.
Step #2 - Create a Dataset
From the Nexadata home screen, select Connect to a Dataset
Provide a unique Name for the data source
Select the Data Connection created in the previous step.
For the Data Format, see that the default format is Tabular.
For the Delimiter, change the setting to Tab.
When the option appears, choose Choose Existing File.
(Note that each Nexadata organization comes with some sample files.)Choose the file "SIMPLE_FACT.txt".
When a file is selected, click Submit to complete the step of creating a Dataset.
👍 Each field will automatically search and filter for a match.
👍 Select the Setup → Datasets to return to the editing interface.
Step #3 - Create a Pipeline
From the Nexadata home screen, select Create a Pipeline.
Provide a unique Name for the pipeline and optionally add a description.
Select the Data Source created in the previous step and see the right-hand grid populate.
Click the Transform button and, using natural language, describe the transformation you'd like to perform.
Filter the Measures column where the value is Sales
Add the following additional transformations:
Filter the Scenario column where the value is BudgetSplit the Product column with a '-' delimiter and name the new columns SKU_Family and SKU_Number
Step #4 - Create a Mapping Group
From the Nexadata home screen, click Create a Mapping Group.
Enter a unique name for the mapping group.
Add the first rule:
Map all 100-level product families to "Colas."
Use the Exact Match option, entering "100" under From and "Colas" under To.
Add the second rule to map everything that is not "Colas" to "Non Colas":
Click Add Rule.
Select Not Exact as the map type.
Enter "Colas" under From and "Non Colas" under To.
Click Save to save the mapping group.
Step #5 - Add a Mapping Group to a Pipeline
From the Nexadata home screen, select Build → Pipeline.
Choose the Pipeline that you have been building in this tutorial.
Select the last step in the Pipeline.
Add a new step to the pipeline by clicking on Mapping.
Select the option to Use Existing Mapping Group.
Choose the Mapping Group created in the previous step.
Click Next, provide a Transformation Name, and select the Column to which mapping should be applied. In this case, choose "SKU_Family".
Click the cycle button to preview rule changes and see the impact of the Mapping Group.
Save the Transformation and see the impact of the Mapping Group.
The impact of the Mapping Group is highlighted with purple column headers.
Step #6 - Apply conditions to a map
Open the Mapping Group created in step #4 (Build → Mapping Groups)
Click Add Column, and in the Name field, enter Year.
(Notice that a new Conditions column will appear in the Mapping Group editor.)Add a condition to the first map in the Mapping Group.
Create a condition in AI Mode by using the ⚡️ button.
Enter a condition in natural language such as:
When Year column is Jan.Remove the default condition and then save the condition.
Save the updated Mapping Group.
To view the results of the conditions, return to the Pipeline created in step #3.
Step #7 - Use Advanced Mode and add some additional transformations
While the previous pipeline remains open, navigate to the last step.
Add an Advanced Transformation.
Transformation Type: Select Rename.
Name: Rename SKU Family
Column: SKU_Family
New Column Name: Product Family
Add another Advanced Transformation: Group By.
Name: Sum Product Family
Columns: Product Family, Year
Aggregation Function: Sum
Aggregation Column: DATA
New Column Name: Sum DATA
👍 Try it on your own: Replace the last transformation in the Pipeline and use natural language with this prompt:
Group by year and Product family and sum the DATA column, creating a new column called Sum Data
Do you get the same results?
Step #8 - Execute the Pipeline
From the Nexadata home screen, navigate to Build → Pipeline.
Select the Pipeline you have been building as part of this tutorial.
Once the Pipeline opens, click Execute.
When prompted to select a dataset, choose Use Default Dataset to follow along with this tutorial.
Click Start Pipeline to begin transforming the data.
In less than a second, the Pipeline will complete. Download the output data and open it with your preferred editor to review the results.
This tutorial is complete. Welcome to Nexadata!