Embedded analytics is rapidly transforming how modern organizations leverage data to drive smarter decisions. By embedding reporting and dashboards directly into business workflows, companies can empower employees with real-time insights to guide actions.
This definitive guide will explore all aspects of embedded analytics in-depth so you can assess if it‘s right for your organization.
What is Embedded Analytics Exactly?
Embedded analytics refers to the integration of reporting and visualization capabilities directly into business applications instead of requiring separate analytics tools.
For example, imagine an ecommerce platform that displays real-time product performance analytics on each product page. Or a support ticketing system showing ticket resolution trend dashboards alongside queues.
Rather than having to log into distinct business intelligence platforms like Tableau, Qlik or Power BI, users access insights within their regular workflows.
According to leading analyst firm Gartner, the defining difference lies in this seamless contextual placement:
"Embedded analytics is distinguished from traditional BI platforms in that analytics are part of a business process where users are already working, versus having to go to a separate tool."
Under the hood, embedded analytics solutions leverage:
- Data integration to ingest, process and store data from source systems.
- Analytics engines that query data and perform calculations.
- Visualization libraries to render metrics in charts, graphs and dashboards.
Vendors package these components into embeddable tools that can integrate using modern APIs, SDKs and widgets. The complexity is masked from end users who simply interact with analytics visually.
The Strategic Benefits Driving Adoption
There are compelling reasons why forward-thinking organizations are embracing embedded analytics:
Increased Adoption & Usability
By providing insights in-workflow rather than requiring users to adopt new tools, adoption rises. No formal training is needed and analytics leverage existing user skills.
According to surveys by enterprise software firm Atlassian, only 29% of employees use their company‘s BI tools. But adoption reaches 48% when analytics are embedded in actual workflows.
Streamlined Decision Making
With analytics seamlessly placed where decisions occur, relevant data-driven insights can guide actions in real-time. Users don‘t have to disrupt workflows to log into separate BI tools.
As a data scientist myself, I‘ve seen firsthand how embedded analytics creates a tight loop for data to inform decisions. Action becomes insight-driven.
Enhanced Internal & External Value
The benefits aren‘t limited to internal teams. Customer-facing analytics also boosts satisfaction and retention as users better understand product value. Partners benefit from transparency as well.
Modern embedded analytics tools allow for flexible custom solutions tailored to unique needs with the right data connections, compliance and controls.
While traditional BI demands significant IT overhead for maintenance and customization, embedded solutions are engineered for low-code self-service access lowering TCO.
According to IT research firm Spiceworks, embedded analytics can reduce BI costs by as much as 25-50% over legacy tools.
Key Differences from Traditional BI
It‘s important to understand how embedded analytics philosophy diverges from traditional BI platforms:
Traditional BI Platforms
- Centralized portal for visualizing data
- IT-driven – requires technical specialization
- Generic dashboards tailored to broad audience
- Users have to come to the platform
- Analytics embedded into real-world workflows
- Enables customizable experiences
- Accessible directly by business users
- Tool comes to the users within environment
Tableau, Power BI and other traditional BI tools still have value for cross-functional reporting. But embedded analytics deliver focused, actionable insights tailored to each user‘s context. The two complement each other in a comprehensive data strategy.
Where is Embedded Analytics Being Used?
Embedding analytics directly into workflows is transforming both digital businesses as well as traditional enterprises:
SaaS platforms, online marketplaces, mobile apps and other digital products are all embedding analytics to display usage and performance directly to customers.
For example, an edtech platform shows enrollment analytics on instructor dashboards. A marketing analytics tool displays campaign metrics to clients. A gaming company allows players to see their gameplay statistics in the app.
This increases product stickiness while providing transparency into how it‘s performing for each user.
Sales & Account Analytics
CRM and account management systems now integrate analytics to arm sales and service teams with client insights in-context.
Instead of relying on stale reports, a rep can see quarterly forecasts, account health scores and other key metrics as they‘re engaging with each client.
Enterprises are leveraging embedded analytics to empower employees across domains including:
- Supply chain managers viewing shipping delays and bottlenecks.
- Support agents monitoring ticket queues and resolution rates.
- Inventory staff tracking real-time out of stock alerts.
OEM & IoT Analytics
Manufacturers are embedding analytics directly into smart devices and equipment including:
- Medical devices tracking patient utilization and diagnosis stats.
- Automobile telematics displaying driving trends and diagnostics.
- Industrial equipment visualizing sensor data for predictive maintenance.
In a survey by Cisco, 90% of enterprises utilizing IoT data are using embedded analytics to extract value rather than raw streams alone.
Key Features to Look For
With a range of solutions available, here are some must-have capabilities:
Flexible Embedding – Support for diverse use cases including portals, mobile apps, internal tools, IoT devices and AI assistants.
Developer Friendly – Clean APIs, SDKs and documentation to accelerate embedded integration by engineering teams.
Governance & Security – Sophisticated controls around data access, filtering, masking and row-level security.
Self-Service Access – Business teams can manage analytics without relying on technical resources.
Interactive Visualizations – Modern visualizations like charts, filters, pivot tables and gauges available out-of-the-box.
Smart Insights – AI-powered analytics like forecasting, anomaly detection, natural language query and sentiment analysis.
Performance & Scalability – Cloud-native infrastructure that handles large data volumes and user loads.
Customizable Branding – Match embedded experiences seamlessly to your product and organization‘s brand look and feel.
Evaluating Leading Software Platforms
Choosing the right embedded analytics platform depends on your organization‘s use cases, technology stack and functional requirements. Here is an overview of leading solutions:
Microsoft Power BI Embedded
Power BI Embedded enables fully interactive Power BI report and dashboard embedding with fine-grained controls. Usage-based pricing and Azure integration make it popular.
- Broad range of visualization functionality
- Template apps for accelerated development
- Granular role-based access controls
- Integration with Azure data and AI services
Ideal For – Microsoft-based organizations wanting an enterprise-ready option.
Recently acquired by Google Cloud, Looker is optimized for embedding analytics into modern web and mobile apps leveraging its powerful modeling and abstraction capabilities.
- SDK support for web, iOS, Android, React
- Live direct database connections
- Sophisticated access control
- Visualization library with advanced analytics
Ideal For – Data-driven SaaS, web and mobile applications.
Sisense is known for its flexibility, performance with large complex data and ability to embed fully white-labelled analytics experiences.
- "Bring your own data" flexibility
- High performance In-Chip engine
- Broad API and integration ecosystem
- Optimized handling of large datasets
Ideal For – Custom analytics use cases with complex data requirements.
Chartio is beloved for its intuitive visual interface for fast and flexible analytics application building. Great for teams needing speed.
- Drag and drop report/dashboard design
- Live query tables with custom SQL
- Lightweight embedding via iFrames
- Broad data connector capabilities
Ideal For – Organizations that value intuitive, fast analytics development.
Grow offers embedded analytics enhanced with natural language search, alerting and notebook style collaborative analysis.
- AI-powered natural language search
- Self-service data analysis workspaces
- Usage tracking and product analytics
- Broad platform integrations
Ideal For – Innovative analytics apps with collaborative analysis.
Key Predictions on Embedded Analytics Adoption
The global embedded analytics market is projected to grow over 17% annually reaching $7 billion by 2026 according to MarketsandMarkets. Key predictions fueling this growth include:
- Wider adoption beyond tech into healthcare, manufacturing, automotive and other traditional industries.
- Platforms leveraging more AI/ML intelligence for automated insights.
- Tighter integration between analytics apps and underlying data infrastructure.
- Expansion into more customer/partner facing analytics use cases.
- Improved access and connectivity to real-time data pipelines.
As organizations become more data-driven, the ability to embed analytics seamlessly across workflows will only increase in strategic value.
Are Embedded Analytics Right For Your Organization?
Based on your specific requirements and use cases, assess if embedded analytics align with your organization‘s needs:
Consider Embedding If:
- You want to increase user adoption of analytics.
- Your team needs faster access to insights.
- Custom analytics apps would add value.
- Client/user self-service analytics would help.
Consider Traditional BI If:
- You have very centralized analytics needs.
- Your users have technical analytics skills.
- IT-driven governance is preferred.
- Standardization is a priority over customization.
For most organizations, an embedded approach can complement traditional BI reporting to provide the right insights to the right users at the right time.
Key Takeaways and Conclusions
Here are my key recommendations on embedded analytics:
- Modern organizations should view embedded analytics as a strategic capability rather than a discrete software feature.
- The ability to contextualize insights aligns analytics investments with real-world business objectives.
- Look for a platform with strong governance, yet easy self-service access for users.
- Start with a focused pilot that demonstrates value before scaling across the business.
- Carefully evaluate leading solutions – integrations with existing technology are key.
As companies continue embracing digital transformation, embedded analytics unlocks tremendous potential to optimize decisions and workflows through data-driven intelligence. Now is the time to leverage embedded analytics capabilities for a sustained competitive advantage.