Key Capabilities
Product Architecture
FineBI 7.0 redefines self‑service analytics—helping enterprises move from data‑rich but insight‑poor to truly data‑driven, where everyone can analyse, decide, and act with confidence.
Through Metrics Hub and Data Catalog, FineBI ensures analytics stay unified, trustworthy, and scalable as they grow.
Data Management
Data management in FineBI covers the entire process of connecting data sources, organizing commonly used datasets, refining business metrics, and making data securely available to business users.
Data Connection
Connect Data is the entry point for bringing data into FineBI. After deployment, BI Administrator links FineBI to the company’s operational databases so the system can read real-time or regularly updated business data. Once the connection is set up, all other parts of FineBI—such as the catalog, metrics, and dashboards—can directly use the data without manual imports.
The Database category provides the following data connections:
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Direct JDBC Connection: This method facilitates direct access to relational databases via JDBC, ensuring efficient and seamless data retrieval.
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JNDI Connection: By utilizing JNDI (Java Naming and Directory Interface), FineReport enables shared data connections with application servers, optimizing resource management in multi-tier environments.
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XMLA Integration: FineReport supports connectivity to multidimensional databases through XMLA (XML for Analysis), allowing users to access and manipulate complex analytical data efficiently.
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SAP System Connectivity via JCO: Leveraging JCO (Java Connector Architecture), FineReport integrates seamlessly with SAP systems, providing direct access to enterprise resource planning (ERP) data for enhanced business intelligence.
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FineDataLink for Data Development: FineDataLink provides a robust framework for data development that streamlines data integration processes and enhances your overall data management capabilities.
Data Preparation
FineBI offers two primary data access modes to suit different business needs and technical requirements:
Live Connection
In this mode, FineBI queries the source database directly without storing any data locally. The data is always current, reflecting the latest changes in the business system. Live Connection relies on the performance of the customer's database or data warehouse and is best suited for environments with a mature data platform, especially when real-time access or high concurrency is required.
Extract
In Extract mode, FineBI pulls selected data from the source database and stores a copy inside its own engine. This enables the system to create cached datasets for fast, in-memory OLAP analysis, which is particularly helpful when working with large data volumes or complex queries. Because the data is copied rather than read in real time, it must be refreshed on a schedule to stay up to date, and this mode also requires sufficient local disk space.
Data Catalog
Once the connection is established, frequently used or foundational tables from the database can be added into the Data Catalog. The catalog serves as a shared repository where high-quality, commonly used datasets are stored for easy access by business teams. If certain tables have inconsistent structure or low data quality, they can be further processed through the Metrics Hub.
What Can Be Added to the Data Catalog?
Excel Dataset
Upload a local Excel file and store it in FineBI as a dataset.
SQL Dataset
Write simple SQL queries in FineBI to preprocess data from the database and add the query result as a dataset.
Database Table
Add an entire database table directly into FineBI without any processing.
Published Self-Service Dataset
Self-service datasets created in Analysis Themes can be published to the Data Catalog for other users to reuse.
Published Metrics
Metrics, dimensions, and metric sets published from the Metrics Hub can also be added to the catalog for unified access during analysis.
Metrics Hub
Metrics Hub serves as a central library for business metrics used across the organization. It stores each metric’s definition, calculation logic, related data fields, and basic business explanation. Instead of keeping metric definitions scattered in different dashboards or teams, Metrics Hub unifies them in one place so everyone can refer to the same version. This helps avoid inconsistent calculations and makes it easier for analysts and business teams to understand what each metric means and how it is produced. In addition, Metrics Hub provides the semantic foundation for FineChatBI, allowing the chat engine to interpret business terms accurately and return answers based on governed, trustworthy metrics rather than ad-hoc calculations
Data Editing
Data Preparation provides a visual environment for shaping raw data into analysis-friendly datasets. Users can connect multiple data sources, merge tables, clean fields, create calculated fields, and adjust data structures—all through an intuitive interface. While the earlier steps in data management are typically carried out by data administrators to set up the overall data foundation of the platform, Data Preparation is the step that happens when an analysis actually begins. It allows analysts to process and reorganize the specific data needed for a particular analysis task, without relying on complex code or engineering support. Once a dataset is prepared, it can be reused in dashboards, charts, and ChatBI.
Dashboarding & Visualization
Dashboarding & Visualization is where users build the actual analytical views that present their data in a clear and structured way. After selecting a dataset, users can create charts by choosing fields and assigning them to axes, indicators, or dimensions. FineBI supports a wide range of visual types—from basic tables and bar charts to line trends, scatter plots, combined charts, maps, and KPI summaries—allowing users to match the chart type to the analytical purpose.
In the dashboard design area, users can freely arrange charts, text blocks, images, and other components on a flexible layout canvas. Each component can be resized, aligned, or grouped to ensure a readable and organized presentation. Dashboards can also include interactive elements such as global filters, slicers, drill-downs, and linkages between charts, enabling readers to explore data from different angles without leaving the page.
For more complex reporting needs, FineBI allows dashboards to be built across multiple pages, creating a structured, chapter-like presentation where different business topics or levels of detail are separated logically. Users can also add explanatory text, titles, and visual highlights to guide readers through the analysis and make insights easier to understand.
Once a dashboard is completed, it can be saved for personal use or shared with others in the organization. Users with access can view it online, interact with filters, or switch between pages, making dashboards a central tool for ongoing business analysis and reporting.
Collaboration & Sharing
Collaboration
When a user needs to edit a dashboard created or shared by another user, FineBI supports collaboration through shared analysis themes. Multiple users can work within the same theme to make edits, adjust components, or continue building the dashboard together.
Dashboard Publish Request
Business users can submit a request to publish their dashboard to the Data Catalog. Once approved, the dashboard becomes visible under the designated catalog folder, and any user who has viewing permissions for that folder can access it directly.
Public Link Sharing
For scenarios where viewers do not have a FineBI account, or are accessed from a device without BI installed, dashboards can be shared via a public link. By opening the link, recipients can view the dashboard without logging into the system.
Internal Sharing to the Catalog
Dashboards can also be shared directly with existing BI users inside the system. Without requiring administrator intervention, a user can choose specific users or groups to share a dashboard with, and those dashboards will appear in the catalog for the selected users.
Security & Permissions
Security & Permissions in FineBI governs how data, dashboards, and metrics are accessed across the organization. The system supports multiple layers of access control, allowing administrators to decide not only who can view or edit a dashboard, but also which datasets, fields, or even rows of data a user is allowed to see. Permissions can be assigned to individual users, user groups, or departments, making it flexible enough to match different organizational structures.
FineBI also enables sensitive data to be hidden at a granular level. Row-level permissions ensure that different users only see the records relevant to their department or role, while column-level rules can mask fields containing confidential information. These controls apply consistently whether the data is used in dashboards, ad-hoc analysis, or ChatBI.
In addition to access control, FineBI integrates with enterprise authentication systems such as LDAP, SSO, and Active Directory, ensuring that user identity and login management align with existing IT policies. Audit logs record key actions—such as who viewed, modified, or shared a dashboard—providing traceability required for internal governance or compliance reviews. Altogether, Security & Permissions ensures that data is shared safely, only with the right people, and always in a controlled and compliant manner.