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

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "In the Filename field, select the persons.csv file you downloaded."

A block of code is set as follows:

-- Lead Source Standardization
case 
when `LeadSource` = 'Patnes' then 'Partners'
when `LeadSource` = 'Diect' then 'Direct'
when `LeadSource` = 'Sales Ceated' then 'Sales Created'
when `LeadSource` = 'efeal' then 'Referral'
when `LeadSource` = 'Self-Souced' then 'Self-Sourced'
when `LeadSource` = 'Maketing Outbound' then 'Marketing Outbound'
when `LeadSource` = 'Stategic Accounts Maketing' then 'Strategic Accounts Marketing'
when `LeadSource` = 'Patneing' then 'Partners'
else `LeadSource` -- If not mapped then keep as is
end

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

SELECT 
DATE(`LastModifiedDate`) as 'Date', 
SUM(case when `IsWon`= 'true' then 1 else 0 end) as 'Won',
-- Lost = Closed - Won
SUM(case when `IsClosed` = 'true' then 1 else 0 end) -
SUM(case when `IsWon`= 'true' then 1 else 0 end) as 'Lost',
SUM(case when `IsClosed` = 'true' then 1 else 0 end) as 'Closed'
FROM `opportunity_cleansed`
GROUP BY DATE(`LastModifiedDate`)
ORDER BY 1 DESC

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: "Python Script is the design tile to drag and drop for use in a dataflow."

Tips or important notes

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