Over the past 10 years, data analytics and data visualization have become essential components of an enterprise information strategy. And yet, the adoption of data analytics has remained remarkably static, reaching no more than 30% of potential users. This book explores the most important techniques for taking that adoption further: embedding analytics into the workflow of our everyday operations.
Authors Donald Farmer and Jim Horbury show business users how to improve decision making without becoming analytics specialists. You'll explore different techniques for exchanging data, insights, and events between analytics platforms and hosting applications. You'll also examine issues including data governance and regulatory compliance and learn best practices for deploying and managing embedded analytics at scale.
• Learn how data analytics improves business decision making and performance
• Explore advantages and disadvantages of different embedded analytics platforms
• Develop a strategy for embedded analytics in an organization or product
• Define the architecture of an embedded solution
• Select vendors, platforms, and tools to implement your architecture
• Hire or train developers and architects to build the embedded solutions you need
• Understand how embedded analytics interacts with traditional analytics
Author(s): Donald Farmer, Jim Horbury
Edition: 1
Publisher: O'Reilly Media
Year: 2023
Language: English
Commentary: Publisher's PDF
Pages: 162
City: Sebastopol, CA
Tags: Machine Learning; Data Analysis; Data Science; Management; Popular Science; Analytics; Decision Making; Compliance; Data Privacy; Data Security; Data Governance
Cover
Copyright
Table of Contents
Preface
Who Should Read This Book
Navigating This Book
Conventions Used in This Book
O’Reilly Online Learning
How to Contact Us
Acknowledgments
Chapter 1. Introduction to Embedded Analytics
Analytics for Business Users and Consumers
What Success Looks Like
Measurable Business Outcomes
Engagement and Adoption
Spreadsheets and Analytics
A Game Plan for Embedded Analytics
Understanding Where You Are
Setting a Goal
Mapping Out the Journey to Success
Chapter 2. Analytics and Decision Making
Executive and Strategic Decisions
Operational Decisions
Tactical Management Decisions
A Design Pattern for the Analytic Experience
Orientation
Glimpsing
Examining
Deciding
Ambiguity and Analytics
Summary
Chapter 3. Architectures for Embedded Analytics
Elements of Embedded Analytics
Data Connectivity
The Analytics Engine
Branding the User Experience
Developer Resources
Scalability
Security
Administration Tools
Embedded Analytics Platforms
Component Libraries
Enterprise Reporting Platforms
Business Intelligence Applications
Purpose-Built Embedded Platforms
Embedded Self-Service
Summary
Chapter 4. Data for Embedded Analytics
CSV and Other Text Files
Operational Data Sources
Analytic Data Sources
Data Warehouses
In-Memory Engines
Data Lakes
Data Integration Pipelines
Writing Back to Sources
Summary
Chapter 5. Embedding Analytics Objects
What Can We Embed?
Key Performance Indicators
Data Visualizations
Tabular Data
Dynamic Text and NLG Content
Adding Interactivity
Interaction Examples
Interaction as a Value-Add
Technical Considerations
Embedding Objects with iframes
Using iframes to Our Advantage
Cross-Domain Limitations
Current Embedded Analytics Trends
Using Embedded Analytics to Share Data
Transformative Best-Practice Visualization
The Look and Feel of Embedded Experiences
Putting It All Together
Embedding Workflow
A Typical Reporting Automation Workflow
Using Embedded Analytics to Power Prescriptive Analytics
Operationalization (or “Write-Back”) of Data
Business Case Integrations
Management and Governance Integrations
Conclusion
Chapter 6. Administration of Embedded Analytics
Deploying Embedded Analytics
On-Premises Deployment
Cloud Deployment
IT Operations and DevOps for Embedded Analytics
Security for Embedded Analytics
Security Priorities for an Embedded Analytics Solution
Open and Closed Systems
Single Sign-on
Summary of Security Practices
Other Administrative Considerations
Scheduling
Version Management
Report Bursting
The Administrative Console
Conclusion
Chapter 7. Governance and Compliance
Governance, Compliance, Security, and Privacy
Privacy and Security
Governance and Compliance
Policies and Practices
If Compliance Is Critical, You Need a Compliance Team
Look for Secondary Benefits of Good Governance
Commit to Openness, Awareness, and Training
Governing Your Governance
A Security and Privacy Cross-Functional Team
Governance in the Cloud
Business Continuity Is a Security and Privacy Issue
Developing a Governance Strategy
Measuring the Success of Governance
Summary
Chapter 8. Beyond the Spreadsheet
Setting the Stage
Let There Be Spreadsheets
Are Spreadsheets Analytics Platforms?
The Ubiquity of Excel
What Excel Doesn’t Do
Almost an Answer
Beyond Excel
Simple Reporting and Analytics
Integration and Collaboration
Project Management and Workflow
Computational Notebooks
Putting Spreadsheets in Context
Choose the Spreadsheet Tool Carefully
Don’t Break the Paradigm of Visual Analytics
Pursue Consistent Methods for Interaction Where Possible
Consider Highly Targeted Use Cases for Tables
Conclusion
Chapter 9. Data Science, Machine Learning, and Embedded Analytics
DSML in Practice
DSML Is Hard
The Power of Storytelling
When Things Go Wrong
The DSML-Driven Call Center
Propensity Modeling
Training a Model
Putting It into Practice
Closing the Loop
Other Typical Use Cases
The Rise of Generative Language Services
Conclusion
Chapter 10. Analytics as a Line of Business
Data as an Asset
Data Products
Product Analytics for Embedded Analytics Technologies
Self-Service as a Feature
Tiering an Analytics Product
Pricing Embedded Analytics
Supporting Embedded Analytics
Launching Your Product
Conclusion
Index
About the Authors
Colophon
