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.
Based on the selected option, enter the required connection details.
When complete, Submit the connection for validation.
To view and edit the created connection, select it from the Setup → Connections dropdown.
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.
In the Data Format, change the delimiter to Tab.
Enter the S3 Bucket name.
Enter the S3 Path.
Click Submit when each field has been entered.
To view and edit the created data source, select it from the Setup → Datasets dropdown.
👍 Each field will automatically search and filter for a match.
👍 Select the Setup → Dataset to return to the editing interface.
Step #3 - Create a Pipeline (Part 1)
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 Map
From the Nexadata home screen, select Create a Mapping Group.
Provide a unique Name for the mapping group.
Add the first Rule to map all 100-level product families to "Colas"
Add the second Rule to map everything that is not "Colas" to "Non Colas". This is done with a Regex statement with the following syntax:
[^Colas].*Click the Save button to save the Mapping Group
Step #5 - Create a Pipeline (Part 2)
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 and provide a Transformation Name, and select the Column to apply mapping. In this case, choose
SKU_Family.Save the Transformation and see the impact of the Mapping Group.
Step #6 - Create a Conditional Map (Part 3)
While the previous pipeline is still open, edit the Colas Mapping created in the previous step.
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 save the condition.
Save the updated Mapping Group in the pipeline.
See that the mapping now only applies to month(s) that meet the condition.
Step #7 - Use Advanced Mode and add some additional transformations
While the previous pipeline is still open, select the last step of the pipeline.
Add an Advanced transformation.
For Transformation Type, select Rename.
Name:
Rename SKU FamiilyColumn:
SKU_Family,New Column Name:
Product Family
Add an additional advanced transformation, Group By.
Name:
Sum Product FamilyColumns:
Product FamilyandYearAggregation Function:
SumAggregation Column:
DATANew Column Name:
Sum DATA
This tutorial is complete. Welcome to Nexadata!