FineBI 6.0 has released, powerful and accessible to everyone.
Improved Analysis Pathway
FineBI 6.0 introduces a new analysis pathway.
Analysis subjects tightly link the data, components, and dashboards required to complete an analysis, providing users with a seamless and immersive data analysis experience.
In version 5.0, modifying a data table while creating a component can be troublesome, but in version 6.0, switching between components and datasets is easier and more cost-effective.
Components now can be displayed as analysis results, improving the efficiency.
Users can practice and learn the workflow of analysis in version 6.0 through First Analysis Example in FineBI.
Public Data serves as a resource for the data analysis of businesses, allowing users to analyze based on these data. Users can also share their data to Public Data.
Before: Users with business package permissions could create self-service datasets under the business package. However, many intermediate tables were also created in the business package, leading to messy data and difficult management.
Now: Authenticated data with higher quality can be stored in Public Data. This avoids messy data created by multiple users in the business package and the difficulty of finding data when needed.
The Sankey diagram visually represents data flow and identifies important components and inefficiencies.
The box plot offers a clear visual representation to help users quickly identify data bias, symmetry, outliers, and distribution.
Users can display trends based on conditions in KPI indicator cards.
FineBI 6.0 enables users to sort and filter fields, modify field names and types, delete columns, and reorder fields by dragging and dropping them in headers. These adjustments enhance users' data management experience.
Data validation let users find and fix issues during analysis. Click the header of coloumns to see summary statistics at the bottom of the table or click to view unique value counts.
Column to row transforms two-dimensional tables into one-dimensional tables. In version 5.0, users need merge multiple tables to achieve this effect. However, with the built-in and optimized function in version 6.0, users can now perform column to row transformation with ease.
A one-dimensional table is also commonly known as a pipeline table. It usually has fixed column names, and data is entered row by row.
A two-dimensional table is a relational table. The values in the data area usually need to be determined by both rows and columns.
If tables share a common key field, users can enrich one table with the other's fields through a join. Click to add fields from Table B to Table A, and then summarize the combined data. This function is similar to Excel's LOOKUP, SUMIF, and SUMIFS functions.
In version 6.0, users can now combine data from two tables through a single join and summarization process, eliminating the need for generating intermediate tables as was required in version 5.0. This enhancement facilitates faster analysis and simplifies workflows.
6.0.3 enhances grouped data analysis with condition-based filtering. Users can now filter summarized data by conditions.
In the Group Condition page, users can add conditions to group the data.
In version 6.0, all analysis processes, including data tables, components, and dashboards, are performed under subjects. This enables easy collaboration and sharing with others when users need to edit or analyze the data together.
6.0 also introduces folder sharing, making it easier for users to collaborate with their team on analysis subjects.
When many data updates are queued but urgent data is needed, the super admin can prioritize emergency updates by clicking Cut In Line.
In subjects, users can apply to publish their own analyzed data tables to Public Data for other users to view or use.
In Version 6.0, users can securely share dashboards using public links with expiration dates to ensure timely restriction of access.
FineBI version 6.0 offers intelligent multidimensional analysis to locate key influencing factors and their impact on indicator values. Analyzing too many dimensions can result in loss of focus, hindering the identification of problem causes. With the data explanation function, users can easily click on an indicator value to reveal the main factors affecting it, enabling targeted dimension analysis, and improving efficiency.
The DEF function enables calculations in complex scenarios, including inter-row and inter-column calculations.
In version 6.0, accidental deletion of crucial analysis resources is no longer a concern. Instead, they will be relocated to Recycle Bin for effortless retrieval, if necessary.
FineBI 6.0 can integrate FineDataLink as a data development module that houses a dual-core engine for both Extract, Load, Transform (ELT) and Extract, Transform, Load (ETL) processes. Its flexibility enables it to handle diverse data processing scenarios, enabling IT personnel to synchronize top-notch data to FineBI efficiently. This integration empowers business personnel to independently perform self-service analytics.
Support offline synchronization, SQL scripts, and data transformation.
Support data extraction from various databases.
Enable the creation, deletion, updating, and reading of data tables within specific databases.
To effectively monitor abnormal data on a daily basis using the dashboard, it is essential to avoid traditional manual monitoring which can be time-consuming and error-prone. While Task Schedule can act as an alert, it adds complexity to admins' management of permissions for different users and is cumbersome for business personnel to operate.
To resolve these challenges, users can install and use the Data Alert plugin to enable business users to create data monitoring independently. The system will send users email notifications once any abnormal data is detected.
Data Portal provides a unified approach to access data queries.
Users can find their favorite and followed reports, system announcements, and updates of reports quickly on the portal homepage.
It helps users improve the efficiency of finding data and reduces communication costs.
Version 5.0 had multiple user types, including view user, design user, process user, and analyze user, leading to challenges for both admins and users. In version 6.0, we streamlined the user logic and narrowed it down to only design user and view user, simplifying management greatly.
Optimized scheduling of calculation threads
In FineBI 6.0, the self-service dataset enables instant output of up to 10 million records.