What is embedded analytics?

Embedded analytics is designed to support business users, allowing them to make better everyday decisions based upon data. It enables self-service analytics in a seamless experience for users within an organization, or for the customers of an application or product. Users can quickly ask questions of their data and uncover meaningful insights without having to leave the environment they use every day. Users can take advantage of self-service tools like data visualizations, interactive dashboards, and reporting to turn insights into action.

Embedded analytics is not new but the technology has continued to evolve and adapt to customer needs over the past 35 years. With a higher rate of adoption than other BI tools, several industry analysts have noted the potential market growth for embedded analytics. They anticipate renewed interest in coming years as organizations look for new ways to leverage their valuable data assets

What is the value of embedded analytics?

Embedded analytics brings the power of BI directly into an existing application's user experience, giving users or customers richer context and fresh information within the operational applications they already know. This insertion of BI within operational or custom applications already used daily increases adoption by users and makes applications more valuable than traditional BI or analytics. Embedded analytics puts data and insights where users need them most, and can lead to further insights and smarter actions.

What are the main benefits of embedded analytics?

Embedded analytics offers many advantages to businesses by allowing organizations to take advantage of their data by offering simple, user-friendly analytic applications.

Here are some of the main benefits organizations can realize through embedded analytics:

• Business Intelligence where users need it: By embedding pixel-perfect reports and dashboards within an application’s User Interface (UI), users will find the insights they need seamlessly, from within the app they’re using. This can lead to increased adoption of BI tools and better decisions as a result of those insights found by users.
• Self-Service Reporting: Reduce the need for analytics and IT support by enabling users to find insights and answers via intuitive, drag-and-drop reporting UIs. With a report and dashboard design environment designed to empower users, they can self-serve what they need without waiting for other teams to provide custom embedded analytics. Therefore, IT teams can focus on other more important tasks instead of ad-hoc requests from business users.
• Improved Customer Experience: For those who are building internal or commercial applications, embedded analytics means your users can get the answers they need without leaving the application. This leads to increased productivity, and an improved customer experience. Embedded analytics integrates the tools users need within the business application, simplifying the user experience and leading to increased customer satisfaction.
• Increased Revenue: Embedded analytics can provide an additional revenue stream for those who use it in commercial applications. Businesses can charge for enabling custom reports. In fact, using embedded analytics in an application can increase the value per user up to 1,250 percent. In addition, it can become a competitive advantage, allowing for a faster time to market for new products.

What are some essential capabilities for embedded analytics?

• Pixel-perfect Reports: Embedded analytics provides pixel-perfect, interactive reports and charts in your app, including on-the-fly sorting, filtering, and formatting of column values and headers. This means that the reports are perfectly formatted to meet any user’s complex requirements.
• Multi-tenant BI: Using a single environment, embedded analytics can allow users to quickly isolate by users, roles, reports, and related permissions to securely separate one customer from another for Software as a Service (SaaS)-based applications. This also allows vendors to manage BI resources and data across multiple customers from a single environment, securely and easily.
• Native Integration with custom Applications: Embedded analytics opens up access to powerful BI services using a JavaScript framework to quickly and easily control the look, feel, and interactive behavior of BI components within the components of the application they are embedded into.
• Interactive Dashboards: With embedded analytics, users can combine interactive reports, charts, and external web content into a single screen to form easy-to-navigate dashboards for your application users.
• Ad-hoc Reporting: By embedding self-service reporting in a business application, businesses allow users to discover their own answers using a drag-and-drop interface that anyone can use. Users of any skill level can create their own reports, dashboards, and visualizations.
• Big Data Connectivity: Use embedded analytics to connect to any JDBC or ODBC data source or connect directly to Hadoop, MongoDB, Cassandra, and more for native reporting and real-time analytics.

What are some major trends for embedded analytics?

Embedded analytics has evolved from its original use cases: operational reporting bundled inside a ERP, CRM, or similar operational application. New embedded analytics spans a number of applications, adds analysis capabilities, places authoring abilities in the hands of end-users, and emphasizes a seamless user experience, including interoperability between the embedded analytics application and the core application.

The following are some trending use cases for embedded analytics:

• Data as a Feature: Everyone knows that you should treat data as an important asset to your business, but not every business treats data as a key component of their applications. Data as a feature basically means designing applications and products that prioritize data as a core element. Ensuring that data is built-in seamlessly within an application is the only way to meet the demands of today’s data-savvy users. Businesses must accept the mindset that applications should be designed to deliver the data users need in an insightful way. This trend has been driven by increasing user demand for intuitive, easy-to-understand application experiences.
• Embedded Analytics Plus Data Science: The challenge many data scientists face is how to operationalize models for real business value. How can an organization deliver the insights found through data science to business users in a way that they can understand and leverage for better decision making? That’s where embedded analytics can help. It can distribute the outputs from your data science models as user-friendly reports and visualizations, embedded directly in the business users’ everyday applications.
• Application and Cloud Architectures: Increasingly complex modern cloud architectures have affected how organizations are deploying embedded analytics. Application architectures have moved to decoupled, lightweight services or microservices. As a result, fewer organizations are embedding heavyweight, monolithic BI applications into these modern, distributed architectures. Instead, expect to see more BI solutions that offer small, specialized BI services, such as embedded analytics, a la carte.