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 reviewed the in-memory data sculpting tools that are available in Domo and how to decide which tool to use. Data Views are the most flexible and powerful but also the more complex to use. Then, there are Data Blends, which allow you to perform VLOOKUPs at scale. Additionally, Beast Modes are a powerful way to extend existing datasets with calculated fields. All of these tools work in the Adrenaline cache, so they are extremely fast. Finally, for those working with datasets with billions of rows, we made you aware of the Adrenaline DataFlows tool for handling data transformation at a mind-boggling scale. Having this in-memory data sculpting power is a key feature that democratizes the process so that an end user doesn't have to wait for specialized resources to assist.

In the next chapter, we will move up from the data transformation layer to the data visualization layer features of the platform, including dashboards.