Welcome to the Alteryx Knowledge Base

Designer Cloud Trifacta Classic is an advanced data management platform that simplifies and accelerates data preparation. With its low-code / no-code ETL capabilities, AI-assisted suggestions, and seamless data integration, it empowers users to connect, transform, and analyze data from diverse sources. By automating data pipelines and promoting collaboration, it reduces time and cost while ensuring data quality. This powerful platform streamlines the path from data to insights, enabling organizations to make informed decisions faster.

Now that you understand how Designer Cloud Trifacta Classic can improve your quality of work life, let’s learn to navigate through the interface to set up a simple data pipeline. 

Navigate Designer Cloud Trifacta Classic on AACP as a New User

Step 1: Locating Designer Cloud Trifacta Classic in AACP
 

• The Alteryx Analytics Cloud landing page is meticulously designed to be user-friendly and familiar. It serves as the entry point for users, providing them with clear call-to-action buttons for specific actions. These actions include advanced data analytics and workflow creation with Designer Cloud Experience, seamless data preparation using Alteryx Designer Cloud Trifacta Classic, automated insights through Auto Insights, data analysis with Machine Learning capabilities, scalable orchestration of data processing and analytics with comprehensive Plans, and robust Reporting functionalities.
• To get started with Designer Cloud Trifacta Classic, click on “Get Started” button on the landing page or locate Designer Cloud Trifacta Classic from the apps icon top left side of screen. 

Step 2: Creating a Flow

• Once in Designer Cloud Trifacta Classic (DCTC) Home page, click the “Flows” button next to “Home” circled in blue to create. The Home page lets you create or access your flows, datasets, and jobs, as well as configure settings and find additional resources. Those additional resources are found at the right side of the Home page circled in blue. Resource(s): 
  • See Home Page documentation for further explanation on what it is.

• The Flows page displays the flows you have access to and lets you create, review, and manage those flows. Resource(s): 
  • See Flows Page documentation for further explanation on what it is.
• You can create a new flow by either:
  • Clicking on ‘Create a flow’ button at the top right of the Home page OR
  • Navigate to Flows page via the top header ‘Flow’ tab (We will use this method in this article) 
    • Once in the Flows page, click on 'Create’ drop-down menu and select ‘Flow.' Resource(s): 
      • See Create Flow Page documentation for further explanation on how to do so.

• To organize your flows in the future, you can create a folder via selecting ‘Folder’ here.

Step 3: Adding a Dataset & Creating a New Connection

• Once in the Flow page, you will see a template that has 3 components, Dataset, Recipe, Output. The first thing to do is to bring in your data.
• Note: Until you bring in your data, the “Recipe’ component will be greyed out. Resource(s): 
  • See Flows Page documentation for further explanation on what it is.
• You can click on either “Connect to your data” object or “+Add datasets” button at the top right to bring up the “Add datasets to flow” window. 

• In the “Add datasets to flow” window, click on “Import datasets” button” circled in blue to add a new dataset .

• You will land on this ‘Import Data and Add to Flow’ window. You can import data from your local files, on-prem, cloud storage, or cloud databases.

UPLOAD LOCAL FILES: To load data from your local files, simply drag them over or click ‘Choose Files’ button to select them from your local instance. Here we have provided a sample demo CSV dataset for you to download and upload. 

Note: The maximum file size allowed for local files is 1GB. Although you can attempt to upload a file size greater than 1GB, an ingestion error will occur. 

Tip: See the resource(s) below for more guidance on the provided demo sample dataset. Resource(s): 

• See ‘DTCTC Example Flow: member info data’ article for more information on how to use the example flow.
• See ‘Sampling’ under ‘General Limitations’ section of the linked Product Limitations documentation. 
• See Overview of Data Import documentation for additional information on uploading, importing of files and of tables. 

• Check your dataset in the Preview window at the top right of your screen. Once satisfied with the uploaded dataset, you can click on “Import & Add to Flow” button at the bottom right of your screen to move to the next step .

UPLOAD DATA FROM DB: To bring in your data from your cloud storages or databases, start by creating a new connection. You can click on the “+ New” button circled in blue.
Note: Users will only be able to see connections they have created or shared connections that other workspace users have created and shared. 

Here in the “Create Connection” module, you can search for our supported connections and set your connection up. 
Note: The ‘Import and Publish’ connection types are connections supported for importing and publishing. Resource(s): 

• See ‘Create Connection’ section of the Connection Types documentation for further explanation on ‘Early Preview’ and ‘I’m interested’. 
• For more information see the ‘Connection Categories’ explore the same documentation. 
• See ‘Introduction to the Designer Cloud API’, ‘Feature Deep Dive – Introduction to Oauth’ , and ‘Feature Deep Dive - Connectivity Via SSH Tunnel’ interactives lessons for further information on establishing specific connections.

Step 4: Creating a Recipe with Transformation Steps

• You can either click on the Recipe object circled in blue, and a panel will appear at the right side of the screen with ‘Edit recipe’ button OR right click on the ‘Recipe’ box to display a list of actions. Both approaches will expose the “Edit Recipe” option to move to the next step.

The Transformer page is where the magic happens. Here you can profile data, interact with data, get suggested transformations, and preview transformations before adding the transformations to your Recipe. The Recipe contains the transformation logic in sequential order. Once in the Transformer page, you can click on either the ‘Search transformation’ icon or the “Add New Step” button circled in blue to bring up the Search Transformations side window. Resource(s): 

• See Transformer Page documentation for further explanation on what it is.

• Here in the Search Transformations side window, you can look for specific transformations from the search bar.

• You can either left click or right click on the Recipe object circled in blue, both approaches will expose the “Edit Recipe” option to click on next. You can also add common transformations from the Transformer Toolbar as circled. The Transformer Toolbar provides quick access to common transformations. Resource(s): 
  • See Transformer Toolbar documentation for further explanation on how to use it

• You can also leverage suggested transformation steps when interacting with the data directly in the Transformation page like so. You can edit the suggestion before you add the step into the recipe as circled in blue.

Step 5: Running a Job

• When you have input the necessary transformation steps into your recipe and wish to run the flow against the full dataset, click on “Run” button circled in blue.

• Tip: Check the publishing settings circled in blue once in the “Publishing action” module so that the settings are aligned to your expectations. Modify the publishing settings to your desired outcome. Once aligned with the settings, click the “Update” button circled in blue to save the any changes made bringing us back to the “Run Job” module.

• To modify the publishing location, publishing format, and publishing action(s), you can hover over a specific publishing action to uncover the “Edit” option once in the “Run Job” window. Click on that option circled in blue to open the “Publishing action” module.

• Before running the job, choose the appropriate Running Environment. 
  • Utilize Trifacta Photon for small and medium-sized jobs up to approximately 1 GB of data being processed in total. 
    • Note: If a larger-sized job is run on Trifacta Photon, the job will initiate but will fail due to limited in-memory processing allocation.
  • Utilize Spark to scale for larger-sized jobs.
    • Note: If a small or medium-sized job is run on Spark, the job will initiate and take a slower time to execute than the leveraging the in-memory processing of Trifacta Photon.

• Once the appropriate Running Environment is selected, click on the “Run” button in the “Run Job” module circled in blue to execute. Resource(s): 
  • See Overview of Data Export documentation for more information on writing to files and tables as well as parameterizing outputs.
  • See Get Results article for more information on running jobs, profiling of results, and publishing results.

Here you can understand how to Navigate Designer Cloud Trifacta Classic on GCP as a New User

Go to the Trifacta Classic Experience Help Docs homepage to navigate the application.