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

Chapter 8: Interacting with Dashboards

One of the useful things a Domo dashboard can do is allow the user to start from a default dashboard view and then interact with its content, exploring the data in real time. The Collections feature organizes the layout of cards on the page into logical sections, almost like organizing slides in a PowerPoint. There are also page filters so that you can filter all the cards on a page at once on any field, including beast modes in the dataset. Once set, filters can be named and saved as a group for reuse. Another advanced feature is interactive card filtering, which, when enabled, sets the page filters for all cards based on what is clicked on in a particular card. In other words, you can use one card to filter the contents of other cards.

In this chapter, we will cover the following topics:

  • Describing dashboard page interactions
  • Working with collections
  • Using page filters