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

Reviewing the in-memory sculpting tools

In Domo, there are several tools for executing data transforms in the Adrenaline cache. These transforms are very performant because they are executed in the cache. They are as follows:

  • Data Views can be used to filter or aggregate dataset data in Adrenaline, just like a typical relational database view. They are also capable of performing some data transformations that may otherwise need to run a dataflow, such as changing data types, removing columns, changing column names, and adding calculations. The Data View's virtual dataset appears in the dataset catalog.
  • Data Blends are basic dataset joins that are equivalent to an Excel VLOOKUP function that's executed in the Adrenaline in-memory cache.
  • Beast Modes are stored calculations on datasets that execute in Adrenaline when a visualization requests the data.
  • Adrenaline DataFlows is an advanced performance tool that's used to run scripted sequential transformation...