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

Understanding how data is stored

All tabular data brought into Domo via connectors, Workbench, or APIs is stored in Vault. Vault is a persistent storage layer that feeds both the in-memory caching engine Adrenaline and the cache optimizer Tundra. Figure 3.1 illustrates these relationships:

Figure 3.1 – Persistent versus in-memory storage

Figure 3.1 – Persistent versus in-memory storage

Vault resides on major cloud infrastructure file services from either AWS or Microsoft Azure. The default cloud service is AWS unless Azure is specifically requested. The physical data is stored and versioned in Vault, regardless of the intake mode (Append or Replace) on the dataset. In Replace mode, previous data versions are no longer queryable from the UI, but they are still stored as an older version of the data. In Append mode, all data versions are queryable because they are linked together as a single entity as illustrated in Figure 3.2:

Figure 3.2 – Dataset version chaining in Domo

Figure 3.2 – Dataset version chaining...