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Data Democratization with Domo

You're reading from   Data Democratization with Domo Bring together every component of your business to make better data-driven decisions using Domo

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781800568426
Length 576 pages
Edition 1st Edition
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Author (1):
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Jeff Burtenshaw Jeff Burtenshaw
Author Profile Icon Jeff Burtenshaw
Jeff Burtenshaw
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Table of Contents (26) Chapters Close

Preface 1. Section 1: Data Pipelines
2. Chapter 1: Domo Ecosystem Overview FREE CHAPTER 3. Chapter 2: Importing Data 4. Chapter 3: Storing Data 5. Chapter 4: Sculpting Data 6. Chapter 5: Sculpting Data In-Memory 7. Section 2: Presenting the Message
8. Chapter 6: Creating Dashboards 9. Chapter 7: Working with Drill Pathways 10. Chapter 8: Interacting with Dashboards 11. Chapter 9: Interacting with Cards 12. Section 3: Communicating to Win
13. Chapter 10: Telling Relevant Stories 14. Chapter 11: Distributing Stories 15. Chapter 12: Alerting 16. Chapter 13: Buzzing 17. Section 4: Extending
18. Chapter 14: Extending Domo with Domo Apps 19. Chapter 15: Using Domo APIs in Python 20. Chapter 16: Using Domo Machine Learning 21. Section 5: Governing
22. Chapter 17: Securing Assets 23. Chapter 18: Organizing the Team 24. Chapter 19: Establishing Standard Procedures 25. Other Books You May Enjoy

Using the Magic ETL Python scripting tile

Access to the Python scripting tile, as seen in the following screenshot, is a paid feature for Magic ETL. Contact Domo to have the tile activated. It enables you to run Python code as part of an inline data pipeline without the need for a Python server, as that is all handled by Domo Magic:

Figure 15.1 – Python scripting tile in Magic ETL

This is a powerful feature to handle edge cases that the standard Magic ETL doesn't cover. To get some experience in using this feature, let's walk through a data cleansing example that can be applied to any category attribute in a dataset, as follows:

  1. Click the DATA main menu icon, then click on the DataFlows icon in the left-side toolbar, then click the ETL icon in the MAGIC TRANSFORM sub-menu.
  2. Change the Add DataFlow Name value to Cleanse with Python.
  3. Click, drag and drop an Input Dataset tile using the Opportunity CH7 dataset, a Python Script tile...
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