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Data Democratization with Domo

Data Democratization with Domo


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.

  • Data Democratization with Domo
  • Contributors
  • About the author
  • About the reviewer
  • Preface
    • Who this book is for
    • What this book covers
    • To get the most out of this book
    • Download the example code files
    • Download the color images
    • Conventions used
    • Get in touch
    • Share Your Thoughts
  • Section 1: Data Pipelines
  • Chapter 1: Domo Ecosystem Overview
    • Introducing the Domo ecosystem
    • Acquiring a data pipeline
      • Intake tools importing data from various data sources
      • Store automatic schema management and performance optimization
      • Data sculpting
      • Outtaking data
    • Presenting the story dashboard
      • Analyzer
      • Beast Mode
      • Dashboards and stories
      • Content distribution
    • Communicating with Domo Buzz
      • Domo Buzz
      • Alerts
      • Profiles
      • Projects and Tasks
    • Extending with apps and APIs
      • Appstore
      • APIs
    • Governing, security, and operations
      • Tools
      • People organizational role design
    • Summary
  • Chapter 2: Importing Data
    • Technical requirements
    • Overview of intaking tools
      • Data sources
      • Tools
    • Importing data from Excel and CSV files
      • Loading your Excel data into the Domo cloud
      • Updating the Excel-based dataset with new data from the spreadsheet
      • Creating a card/dashboard from the dataset
    • Importing data from Google Sheets
      • Loading your Google Sheet data into the Domo cloud
    • Importing data from email attachments
    • Importing data from cloud apps
    • Importing data from databases
    • Importing data from on-premises systems
      • Downloading the Workbench agent
      • Adding a Domo account to Workbench
      • Adding a DataSet job to upload an Excel file
      • Adding a DataSet job to upload an ODBC query result
    • Using federated data connections
    • Using Webforms
      • Creating a Webform dataset
      • Editing a Webform dataset
    • Taking data from Domo
      • Using ODBC to query Domo datasets
      • Using the CLI to query Domo datasets
      • Using the Domo Google Sheets add-on to consume Domo datasets
    • Summary
    • Further reading
  • Chapter 3: Storing Data
    • Technical requirements
    • Understanding how data is stored
    • Finding datasets
    • Working with the properties of a single dataset
      • Using the OVERVIEW tab
      • Using the DATA tab
      • Using the CARDS tab
      • Using the SETTINGS tab
      • Using the LINEAGE tab
      • Using the HISTORY tab
      • Using the PDP tab
      • Using the ALERTS tab
      • Using the dataset OPTIONS actions menu
    • Working with properties of multiple datasets
    • Summary
    • Further reading
  • Chapter 4: Sculpting Data
    • Technical requirements
    • Introducing the sculpting tools for persistent datasets
    • Using ETL dataflows
      • Creating an ETL dataflow
    • Using the DataFlows page
      • Using the DataFlow Detail page
    • Using SQL dataflows
      • Creating a SQL dataflow
    • Summary
    • Further reading
  • Chapter 5: Sculpting Data In-Memory
    • Technical requirements
    • Reviewing the in-memory sculpting tools
    • Using Views Explorer
      • Touring the Views Explorer page
      • Creating a Data View
    • Using Data Blend
      • Creating a Data Blend
    • Leveraging Beast Mode
      • Touring Beast Mode Manager
      • Adding Beast Mode columns to a dataset
      • Finding, editing, and archiving dataset Beast Modes
    • Adrenaline DataFlows
    • Summary
    • Further reading
  • Section 2: Presenting the Message
  • Chapter 6: Creating Dashboards
    • Technical requirements
    • Navigating dashboards
      • Working with the dashboard panel
      • Using the Pages Menu feature
      • Using the dashboard page
    • Working with Analyzer
    • Creating/editing cards
      • Creating a monthly sales trend card
      • Creating a sales target gauge card
      • Creating a sales period over period breakdown card
      • Adding a forecast to a card
      • Creating a pipeline running total card
      • Creating a waterfall card
      • Sculpting the data
      • Creating the waterfall card
    • Summary
    • Further reading
  • Chapter 7: Working with Drill Pathways
    • Technical requirements
    • Creating card drill paths
      • Creating a drill-down to a region from the Sales Attainment card
      • Creating drill-downs on sales actuals and targets
    • Creating a drill-down to a different dataset
    • Linking cards
    • Comparing parts to the whole with segments
    • Summary
    • Further reading
  • Chapter 8: Interacting with Dashboards
    • Technical requirements
    • Describing dashboard page interactions
    • Working with collections
      • Moving cards into collections
    • Using page filters
      • Using the page date filter
      • Using interactive card filtering
      • Adding a filter card to a page
    • Summary
    • Further reading
  • Chapter 9: Interacting with Cards
    • Technical requirements
    • Describing card interactions
    • Using card interactions
      • Working with card filters
      • Using quick filters
      • Using the date range selector
      • Using range zoom
      • Creating chart annotations
      • Using the chart legend to filter
    • Using pivot tables
    • Exporting data to Excel
    • Summary
    • Further reading
  • Section 3: Communicating to Win
  • Chapter 10: Telling Relevant Stories
    • Technical requirements
    • Using a business model framework to be relevant
      • Resources
      • Operations
      • Value Creation
      • Customer Experience
      • Risk
    • Deciding on a story to tell
    • Using a monitoring dashboard to refine story statements
      • Creating a quarterly target variance trend card
      • Creating a regional target variance card
      • Creating a regional quarterly target variance trend card
      • Creating a regional actual sales variance card
      • Creating an actual sales prior year variance card
      • Creating a regional year-over-year quarterly actual sales variance trend card
      • Creating a leaders and laggards card
    • Learning about storytelling patterns
    • Applying a storytelling pattern using Domo Stories
      • Implementing a storytelling pattern
      • Housekeeping
    • Further reading
  • Chapter 11: Distributing Stories
    • Technical requirements
    • Understanding the content distribution landscape
    • Sharing pages
    • Sharing cards
    • Distributing via email
      • Option 1 Schedule as Report
      • Option 2 Send Now
      • Option 3 Send / Export
    • Embedding in productivity apps with plugins and add-ons
    • Using the mobile app and widget
    • Publishing via a URL
    • Creating digital wallboards
    • Embedding in a web page
      • Understanding the Domo Everywhere product family
    • Summary
    • Further reading
  • Chapter 12: Alerting
    • Technical requirements
    • Defining an alerting strategy
    • Understanding the Alert Center
    • Setting alerts on a card
      • Sharing alerts
    • Setting alerts on a dataset
      • Creating a supporting materialized view for the alert
      • Creating a project for the tasks
      • Creating a dataset alert
      • Using alerts to invoke actions
    • Discovering management chain alerts
    • Summary
    • Further reading
  • Chapter 13: Buzzing
    • Technical requirements
    • Learning the Buzz menu options
    • Using the Universal Compose feature
    • Leveraging Social users
    • Understanding the Buzz Navigation pane
    • Touring the Buzz Conversation pane
    • Discovering the Buzz Conversation Detail pane
    • Summary
    • Further reading
  • Section 4: Extending
  • Chapter 14: Extending Domo with Domo Apps
    • Technical requirements
    • Understanding Domo application development architecture
    • Setting up the Domo development environment
    • Creating a Domo app in Domo Dev Studio
    • Publishing a Domo app
      • Publishing an app to a single Domo instance
      • Publishing an app to the Domo Appstore
    • Summary
    • Further reading
  • Chapter 15: Using Domo APIs in Python
    • Technical requirements
    • Using the Magic ETL Python scripting tile
    • Using the Domo Python SDK
      • Setting up Python for Domo
      • Coding and running a Python project
    • Summary
    • Further reading
  • Chapter 16: Using Domo Machine Learning
    • Technical requirements
    • Understanding the AutoML process
    • Training a Domo AutoML model
    • Deploying a Domo AutoML model
    • Supporting Jupyter Workspaces
    • Summary
    • Further reading
  • Section 5: Governing
  • Chapter 17: Securing Assets
    • Technical requirements
    • Considering the dimensions of a security policy
      • Data access culture
      • Decision power-sharing culture
      • Data utility roles
      • Organizational structures
    • Governing people, groups, and roles
      • Using the People page
      • Setting trusted attributes
      • Using the Groups page
      • Using the Roles page
      • Using the Activity log page
      • Using the Licenses page
    • Securing content
      • Understanding the Cards page
      • Understanding the Pages page
      • Understanding the Scheduled Reports page
      • Using PDP
    • Leveraging the authentication standards
      • Reviewing the Authentication page
      • Reviewing the OpenID Connect (SSO) page
      • Reviewing the SAML (SSO) page
      • Reviewing the Access tokens page
    • Controlling network security
      • Authorized domains
      • IP address whitelisting
    • Configuring the company settings
    • Managing the feature settings
      • Configuring Domo Everywhere
      • Certifying content
      • Administering slideshows
      • Administering Buzz
    • Using more admin features
      • Managing easy links
    • Handling PII in Domo
      • Understanding the Anonomatic partnership with Domo for PII
    • Summary
    • Further reading
  • Chapter 18: Organizing the Team
    • Understanding best practices for a Domo organization structure
    • Considering the implications of size on an organizations structure
    • Reviewing the organization's structure roadmap
    • Hiring for Domo team roles
      • MajorDomo job description
      • Domo Master job description
      • Data Specialist job description
      • Sample organization chart
    • Summary
    • Further reading
  • Chapter 19: Establishing Standard Procedures
    • Technical requirements
    • Establishing ownership
      • Determining page ownership
      • Determining card ownership
      • Determining beast mode ownership
      • Determining Dataset ownership
      • Determining DataFlow ownership
    • Implementing certification
      • Implementing the card certification process
      • Implementing the dataset certification process
      • Submitting certification requests
    • Accepting new content requests
      • Handling an issue request
    • Managing content backlog
    • Migrating artifact changes to production
    • Summary
    • Further reading
    • Why subscribe?
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