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


In this chapter, we learned about the Domo app development architecture and that we can leverage all that infrastructure using the Domo Dev Studio utility to create app designs in HTML, CSS, and JavaScript. Application templates are provided to accelerate the client development process with a real-time updating web service to facilitate design creation. App designs are published to the Domo Asset Library instance and deployed as app cards within an instance. We can also apply to have our custom apps published in the Domo Appstore. We created a simple app to display a YouTube video, and published and deployed it as an app card. Additional project samples using the D3 graphics library, connecting to Domo datasets, and doing CRUD operations are provided in the Git repository for those looking to get more advanced examples.

In the next chapter, we will take a foray into Domo's machine learning capabilities.