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

Using SQL dataflows

SQL dataflows is a tool for those of you who know the SQL scripting language. It enables you to chain multiple sequential SQL commands into a transformation pipeline. Domo datasets are the only supported inputs, and the output is one or more datasets. Let's go through the steps of how to create a SQL dataflow.

Creating a SQL dataflow

Let's walk through a scenario where we must create a SQL dataflow to produce a new aggregated dataset that supports burnup charting:

  1. Click on the DATA item in the Domo main menu bar.
  2. Click SQL in the MAGIC TRANSFORM area.
  3. Enter Opportunity Aggregate in the DataFlow Name & Description box.
  4. In the Input DataSets area, click SELECT DATASET.
  5. Click Opportunity Cleansed in the Select a Dataset popup.
  6. Click the CHOOSE DATASET button.

At this point, the page should look as follows:

Figure 4.13 – SQL dataflow with an input dataset

Figure 4.13 – SQL dataflow with an input dataset

Let's add the Date...