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)
1
Section 1: Data Pipelines
7
Section 2: Presenting the Message
12
Section 3: Communicating to Win
17
Section 4: Extending
21
Section 5: Governing

Overview of intaking tools

The Domo platform greatly simplifies the process of getting structured data into the cloud; well, that is, after you have identified the right Domo tool for doing so. The data's source, volume, and security are key factors to selecting the right tool. The destination for all structured data coming into Domo is the dataset. The following figure illustrates some of the many options for data intake:

Figure 2.1 – Intake pathways into Domo

Figure 2.1 – Intake pathways into Domo

Let's look at the sources of data that can be used for import.

Data sources

Here are brief descriptions of the supported data sources:

  • Cloud applications are applications such as Salesforce that run in the cloud, or pretty much any SaaS app with a data API. Connectors also can bring in files from email attachments, cloud databases such as Snowflake, and even public data sources such as census data or RSS feeds.
  • Local files are Excel, CSV, JSON, and XML files...