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Data Watcher 1.20
Data Watcher 1.20
  • 🚀GETTING STARTED
    • What is Primeur Data Watcher
    • Main features of Primeur Data Watcher
    • Navigate through Primeur Data Watcher
  • 🔶MODEL
    • Modeling Dataflows
    • Dataflow Model lifecycle 🚀
    • Dataflow Modeler 🚀
      • Dataflow Modeler toolbar
      • Dataflow Properties panel
      • Node Properties panel
      • Matching Criteria
      • Cut-offs 🚀
      • Notifications 🚀
      • Dataflow Model attributes
  • 🕒MONITOR
    • Dataflow Inquiry 🚀
      • Dataflow Inquiry options 🚀
      • Levels of detail of the dataflow 🚀
    • Dataflow Instance attributes
    • Cut-off Board 🚀
  • DESIGN
    • Configure Dataflow attributes
    • Save and share queries
  • 🧐TROUBLESHOOTING
    • Data Watcher users 🚀
    • Data Watcher Engine extended downtime vs missing events and/or dataflows
    • How to run searches in Data Watcher
    • Data Watcher MongoDB scripts
      • Back up the Data Watcher MongoDB 🚀
      • Restore the Data Watcher MongoDB 🚀
      • Clean up the Data Watcher MongoDB
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  • Why is it useful to model dataflows?
  • What are the main features of dataflow models?
  • What are the steps to model dataflows?
  1. MODEL

Modeling Dataflows

PreviousNavigate through Primeur Data WatcherNextDataflow Model lifecycle 🚀

Last updated 16 days ago

Why is it useful to model dataflows?

Modeling dataflows improves efficiency, security, and control over their processes.

Naming and structuring a dataflow makes it easier to manage and monitor. The use of notifications ensures rapid response to errors, minimizing disruption and operational risk. Assigning attributes organizes workflows more effectively, and aligns tasks with business goals. Configuring cutoff points helps control dataflow behavior and prevents issues. In addition, dataflow modeling improves searchability and user management by enabling selective access and enhancing security, governance, and compliance. Overall, it results in more efficient, reliable, and well-governed business operations.

What are the main features of dataflow models?

Dataflow modeling includes:

  1. labeling specific business flows so that they are easily recognized

  2. managing the arrival of files

  3. processing files on specific nodes through cut-offs

  4. defining dataflow matching rules

To search for dataflow models, use the page.

What are the steps to model dataflows?

Dataflow models can be created from a flow already in Data Watcher or from scratch.

Create a dataflow model from a flow already in Data Watcher

Follow these steps:

  1. Go to the Inquiry section, and click the 3-dot icon on the right of the dataflow.

  2. Select the Model as flow entry.

  1. The Dataflow Modeler page will open loading the selected flow.

  2. Define rules as detailed in the page.

  3. Enter a Business Name for the Model. Note: The Model name must have at least 5 characters.

  4. Click the Save button to confirm. The model will be created in draft status.

Create a dataflow model from scratch

Follow these steps:

  1. Go to Dataflow Models, and click the NEW button.

  2. In the Dataflow Modeler page, click the + button in the bottom-right corner and start drawing the model by dragging nodes from the Add new node panel and dropping them on the board.

  1. To connect nodes, click the dot on the right of the box and drop the line to the dot on the left of the other node.

The line will become an arrow, as in the following figure.

  1. Enter a Business Name for the Model. Note: The Model name must have at least 5 characters.

  2. Click the Save button to confirm the creation of a Model in Draft status.

The list of existing models appears by going to Design > Dataflow Models.

🚀 The Dataflow Models page lists existing dataflow models, together with the indication of whether they are a Master or a Draft version, the number of matching criteria they have, dataflow and cut-off notifications, and their status.

If you are looking for specific dataflow models, use the Filters panel on the right to run a query with specific criteria such as the name of the Model, the notification status (ON or OFF), the name of the node where the Model was created, the type of node (Data One, Spazio, FTP, SFTP, etc.), or the dataflow attribute.

By clicking the 3-dot icon on the right of the row, a menu will appear with options to enable or disable Dataflow/Cut-off notifications, view the master version or edit the draft version on the Dataflow Modeler page.

Note that the status of the Dataflow or Cut-off notifications can be enabled or disabled also when having multiple models selected. In this case, go to the Select drop-down list and choose the option you need.

Define rules as detailed in the page.

🔶
Matching Criteria
Dataflow Modeler
Matching Criteria