Book Image

Data Democratization with Domo

By : Jeff Burtenshaw
Book Image

Data Democratization with Domo

By: Jeff Burtenshaw

Overview of this book

Domo is a power-packed business intelligence (BI) platform that empowers organizations to track, analyze, and activate data in record time at cloud scale and performance. Data Democratization with Domo begins with an overview of the Domo ecosystem. You’ll learn how to get data into the cloud with Domo data connectors and Workbench; profile datasets; use Magic ETL to transform data; work with in-memory data sculpting tools (Data Views and Beast Modes); create, edit, and link card visualizations; and create card drill paths using Domo Analyzer. Next, you’ll discover options to distribute content with real-time updates using Domo Embed and digital wallboards. As you advance, you’ll understand how to use alerts and webhooks to drive automated actions. You’ll also build and deploy a custom app to the Domo Appstore and find out how to code Python apps, use Jupyter Notebooks, and insert R custom models. Furthermore, you’ll learn how to use Auto ML to automatically evaluate dozens of models for the best fit using SageMaker and produce a predictive model as well as use Python and the Domo Command Line Interface tool to extend Domo. Finally, you’ll learn how to govern and secure the entire Domo platform. By the end of this book, you’ll have gained the skills you need to become a successful Domo master.
Table of Contents (26 chapters)
Section 1: Data Pipelines
Section 2: Presenting the Message
Section 3: Communicating to Win
Section 4: Extending
Section 5: Governing

Using the DataFlows page

The DataFlows page is where data transformations are managed in Domo.

Once a dataflow has been saved, it is administered through the DataFlows page, as shown in the following screenshot:

Figure 4.7 – Browsing DataFlows

To search the list of dataflow names, follow these steps:

  1. Click inside the Search field and enter op to see all datasets in the list with op anywhere in their name.
  2. To filter the list of dataflow names by type, click on the ADD FILTER area.
  3. Select DataFlow Type and click Magic ETL to see all the dataflows that were created using the Magic ETL tool.

To save the filter options as a favorite for future use, follow these steps:

  1. Click on the favorite star icon to the far right in the search bar.
  2. Enter the name of your filter – in this case, Magic ETL DataFlows – and click SAVE.
  3. Apply the filter by clicking on it in the FAVORITE FILTERS area.

To apply one...