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 organization's structure roadmap

Organizations rarely stay static, and this is true for analytics teams supporting an organization. Consequently, we should expect the best-fit organizational structure for our analytic teams to change over time, as seen in the following diagram:

Figure 18.3 – Organization structure evolution roadmap

Figure 18.3 – Organization structure evolution roadmap

Fortunately, we can use Figure 18.3 as a quick way to determine whether our current program's size and scope match the right organizational evolution for the program's current state. For example, if the program has several people supporting one group such as a marketing department or sales team, then a reporting structure of a single MajorDomo with several technical specialists would be a good fit.

However, as the team grows to support many groups and has many people, then it makes sense to have multiple MajorDomos for regions or product lines, each with its own Data Specialists organized...