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

Supporting Jupyter Workspaces

Domo added the capability to run Jupyter Workspaces in the Domo cloud, which supports Python3 and R scripting. Setting up the Jupyter cloud environment is automatic and provides full access to the JupyterLab interface for interactive exploratory computing. This is a beta feature, so you will need to work through your Domo Account Manager to get access.

Once activated, follow these steps to access the Jupyter cloud workspace:

  1. Choose the DATA option via the main menu. Then, click the side menu option and choose Jupyter Workspaces, as shown in the following screenshot:

Figure 16.11 – Jupyter Workspaces access

  1. Click + NEW WORKSPACE and enter My Notebook as the workspace's name.
  2. Click SELECT DATASET under DATASETS > Inputs and select Python_Oppty. Then, click CHOOSE DATASET, as shown in the following screenshot:
Figure 16.12 – Adding inputs to a Jupyter Workspace

Figure 16.12 – Adding inputs to a Jupyter...