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What is embedded business intelligence software?

Embedded business intelligence software enables enterprise users to quickly implement self-service data analysis and quickly modify or adjust the analysis results. Embedded BI software allows all team members to easily convert data into value. An open architecture, highly flexible and extensible platform enables users to accurately analyze data and quickly adapt to future changes in analysis requirements.

Embedded BI software is the best choice for enterprises of all sizes. Companies with large data sets can leverage embedded data platforms for business data analysis without straining data resources and other applications. Enhance the analysis ability of ERP, OA, CRM, MES and other business systems, and provide users with the ability to create in-depth analysis reports and charts by themselves. This is where embedded business intelligence software fully embodies its strength.

Embedded BI is critical for small and medium-sized companies when they need to integrate disparate data sources into a data platform that provides perfect business analytics support. In summary, embedded business intelligence software is built specifically for integration with processes, portals, and applications. Integrating business intelligence software functions, such as dashboards, reports, visualization and analysis, into existing applications, which can be easily accessed within applications for business users to use and analyze and enhance the analysis capability of business software, is the trend of the development of business software functions, and is the real demand of users.

Embedded business intelligence software reduces the time required to generate data, thus providing more efficient analysis. It allows users to make data-driven decisions within an application’s workflow without having to navigate to other applications. Using the embedded BI platform can provide advanced reporting and analysis without the time and expense of building it. In other words, embedded BI products can provide analytical capabilities in the context of business applications.

What are the characteristics of embedded business intelligence software

  • Portal capabilities: Provides a Web-based analytics portal that allows users to create, delete, and reorder personal workspaces, add and delete content, and modify page layouts.

  • Visualization: Analyze business data relationships and patterns through rich visualization components.

  • Web analysis reports: Provides OLAP analysis capabilities, providing complete data building, loading, organizing, viewing and saving, and sharing of reports.

  • Map visualization: Provide geospatial mapping information and include the results of geospatial analysis in reports.

  • Mobile business Intelligence: Supports mobile device access and adaptation, and provides mobile monitoring of key indicators and analysis capabilities.

  • Query analysis: Provides query functions for users of all levels across multiple business systems and multiple data sources.

  • Flexible deployment options: Quickly integrate business intelligence into existing IT device environments, supporting mainstream deployment environments such as Windows, Linux, and Docker.

  • Self-service: Allows business users to load, process, and analyze data from any Angle to discover problems and new opportunities.

  • Multi-tenant: Provides customization flexibility for ISVS; Fully multi-tenant.

  • Rich API: Provides rich API interface capabilities that can be embedded in applications in a variety of ways.

  • Data modeling: Provides visual data modeling capabilities to reconstruct data and extract insights quickly and accurately.

  • Shared collaboration: Dashboard analysis results can be shared and controlled by permission within the organization.

  • Data consolidation: Create consolidated views of data for business users across multiple data sources and enterprise applications.

  • Data exploration: Helps analysts discover new insights through interactive operations such as data drilling and linkage.

What are the key performance indicators of embedded business intelligence software

There are several important KPIs to watch for embedded BI:

  1. Can be integrated

When embedded business intelligence capabilities are integrated into business applications, users can access dashboards, visual files, and reports.

  1. Wo ability

Embedded business intelligence software enables developers to white-label and seamlessly integrate analytics to match the look and feel of any given application.

  1. Visual ability

Users can create reports and other user-friendly visualizations to better illustrate the data and gain a competitive advantage.

  1. Data modeling capability

Support self-service data modeling, mixing, and discovery processes. These advanced analytics capabilities enable users to get a high-level view of the data and understand it well.

What are the benefits of embedded business intelligence software

Embedding BI into core applications and business processes has many benefits:

  • Accelerate the development speed: shorten the function development time, promote the application software visual analysis function to market as soon as possible, create value;
  • Reduce initial cost: Reduce the cost of pure code development for analysis functionality;
  • Reduce overhead costs: maintain, upgrade, and support analytics capabilities;
  • Lower opportunity cost: Adhere to the core competitiveness of the development and support;
  • Competitive advantage: provide advanced analytical technology;
  • Data consolidation: ability to combine dynamic data with other data sources;
  • Optimizing business processes: Alerts individuals when performance exceeds predefined thresholds and triggers alerts, workflows, and tasks to optimize processes and performance;
  • Make BI more pervasive: Offer the benefits of BI to more users without having to buy BI tools for each user;
  • Make BI more flexible: BI services can be more easily integrated into new and existing applications, avoiding technical bottlenecks in report and dashboard development;
  • Form a closed loop: Embedded BI integrates operational and analytical functions to enable data information to drive decisions in a virtuous cycle, helping companies better understand what drives their business and adapt more quickly to changing market conditions.

What are the latest trends in embedded business intelligence software

Over the past few years, data has become a core element of organizations. Embedded BI trends will have a greater impact on the entire field of analytics:

  • Collaborative analytics: Data-driven decision making and culture will drive collaborative analytics and value creativity across the organization to drive the business forward.

  • Self-service data preparation: As big data becomes decentralized and integrated across many aspects of the organization, all users need to be able to process their own data.

  • The transition to the cloud will accelerate: cloud platforms will provide a faster, more scalable solution and platform environment.

  • Growth in the value of predictive analytics projects: An increase in the variety of sensors, algorithms, and technologies that will help organizations capture and predict upcoming events. For example, predictive analytics can predict the production environment in real time by connecting data collected by Internet of Things (IoT) devices.

  • Artificial intelligence (AI) : BI technology combined with AI technology, machines will perform tasks normally performed by sophisticated human intelligence.

How to choose the right embedded business intelligence software

In order to achieve higher application utilization, higher user satisfaction, cost and time savings, and potential revenue growth through increased embedded analytics capabilities, the following are key considerations when choosing embedded BI:

  • Security: Ensure that data can be controlled by security permissions at the organization’s multi-tenant and role levels.
  • Customization capability: provides different types of API sets, custom visualizations, plug-ins, CSS customization, etc.
  • Requirement matching: The degree to which embedded BI’s product capabilities meet application enhancement analysis requirements, customer or project requirements.
  • Function: The perfection and satisfaction of product functions, including data source support, data modeling ability, data visualization ability, API interface richness, granularity of permission control, etc.
  • Integration capability: The openness and depth of application and embedded BI integration is mainly reflected in the integration method and API capability.
  • Product architecture: Determine scalability and performance requirements.
  • Budget cost: product cost and licensing model.
  • OEM capabilities: Provide white label analysis to ensure a seamless experience for end users.
  • Integration time: Embedded solutions should take days or weeks, not months.
  • Training and support: What training and other resources are provided by BI vendors to support the embedding of analytical capabilities in applications.

Develop reading

If you’re interested in embedded business intelligence, learn more about Wyn Enterprise. Through flexible data interaction and exploration and analysis capabilities, as well as OEM white standard integration, it fully meets the data analysis requirements of industry applications. It provides multi-source data integration, report statistics, data visualization, self-service BI analysis, data filling and other functions, helping users to mine the potential value of data and providing data support for managers to make decisions.