User Behavior Analysis and Built-in Datasets

1. Overview of User Behavior Analysis

User behavior analysis refers to the function of collecting and analyzing the usage of all users and user groups in the system based on metadata such as operation traces/behaviors on the Guanyuan Data BI platform.

2. Value of User Behavior Analysis

• Helps IT/operation and maintenance departments responsible for on-premises deployment to quickly understand and analyze the usage of business personnel on the current BI platform.

• Helps IT/operation and maintenance departments, or departments responsible for security monitoring/information security auditing, to completely and conveniently record internal data access operations and behaviors, build a security monitoring and information security auditing mechanism, and effectively protect enterprise data assets.

3. User Behavior Analysis Functional Modules

Currently, the user behavior analysis function mainly consists of two modules: built-in datasets and built-in dashboards.

3.1 Built-in Datasets

Through the underlying database and web requests, we have constructed 8 major built-in datasets for user behavior analysis. These datasets are fully updated daily (T+1).

In on-premises deployment environments, no user has permission to modify, delete, or rename these datasets (not even administrators or owners). However, users can perform secondary development based on these datasets to customize the user behavior analysis logic required by the enterprise.

3.1.1 builtin_execute_record Table

This table is extracted from the underlying MySQL database and is used to store the execution status of datasets and ETL tasks.

Table Name	Field Name	Field Type
builtin_execute_record	Domain	STRING
	Resource ID	STRING
	Resource Type	STRING
	Start Time	TIMESTAMP
	End Time	TIMESTAMP
	Duration	LONG
	Status	STRING

3.1.2 builtin_user Table

This table is extracted from the underlying MySQL database and is used to store user records.

Table Name	Field Name	Field Type
builtin_user	Domain	STRING
	User ID	STRING
	Mobile	STRING
	Email	STRING
	Account	STRING
	Account Type	STRING
	Created Time	TIMESTAMP
	Last Modified Time	TIMESTAMP
	User Attribute	STRING
	Custom Role	STRING
	User Status	STRING

3.1.3 builtin_card Table

This table is extracted from the underlying MySQL database and is used to store card records.

Table Name	Field Name	Field Type
builtin_card	Card ID	STRING
	Domain	STRING
	Parent Card ID	STRING
	Dataset ID	STRING
	Creator ID	STRING
	Card Name	STRING
	Card Type	STRING
	Chart Type	LONG
	Created Time	TIMESTAMP
	Last Modified Time	TIMESTAMP
	Page ID	STRING

3.1.4 builtin_page Table

This table is extracted from the underlying MySQL database and is used to store page records.

Table Name	Field Name	Field Type
builtin_page	Page ID	STRING
	Domain	STRING
	Folder	STRING
	Creator ID	STRING
	Page Name	STRING
	Created Time	TIMESTAMP
	Last Modified Time	TIMESTAMP
	Page Type	STRING

3.1.5 builtin_data_flow Table

This table is extracted from the underlying MySQL database and is used to store ETL-related records.

Table Name	Field Name	Field Type
builtin_data_flow	ETL ID	STRING
	Domain	STRING
	Creator ID	STRING
	Folder	STRING
	ETL Name	STRING
	Input Dataset	STRING
	Output Dataset	STRING
	Run Count	INT
	Successful Run Count	INT
	Last Run Duration	LONG
	Status	STRING
	Created Time	TIMESTAMP
	Last Modified Time	TIMESTAMP
	Scheduled Update Time	STRING
	Update Method	STRING
	Last Run Time	TIMESTAMP

3.1.6 builtin_data_source Table

This table is extracted from the underlying MySQL database and is used to store dataset-related records.

Table Name	Field Name	Field Type
builtin_data_source	Dataset ID	STRING
	Domain	STRING
	Creator ID	STRING
	Folder	STRING
	Dataset Name	STRING
	Row Count	LONG
	Column Count	INT
	Scheduled Update Time	STRING
	Status	STRING
	Created Time	TIMESTAMP
	Last Modified Time	TIMESTAMP
	Dataset Type	STRING
	Last Run Time	TIMESTAMP
	Data Extraction Method	STRING

3.1.7 user_and_user_group_relation_record Table

This table is extracted from the underlying MySQL database and is used to store records of user and user group relationships.

Table Name	Field Name	Field Type
user_and_user_group_relation_record	User ID	STRING
	User Name	STRING
	User Group ID	STRING
	User Group Name	STRING
	Parent User Group ID	STRING
	Parent User Group Name	TIMESTAMP

3.1.8 user_behavior_analysis_record Table

This table is generated by recording Request information initiated by the web Http, and is used to store detailed records of user and user group operations.

Table Name	Field Name	Field Type
user_behavior_analysis_record	Operation Time	TIMESTAMP
	Domain	STRING
	Operation Name	STRING
	User Name	STRING
	User Group Name	STRING
	Resource ID	STRING
	Resource Type	STRING
	Resource Name	STRING
	Login Method	STRING
	Client OS	STRING
	Client Browser	STRING
	User ID	STRING
	Client IP	STRING

3.1.9 builtin_directory Table

This table is extracted from the underlying MySQL database and is used to store records related to various system folders.

Table Name	Field Name	Field Type
builtin_directory	Folder ID	STRING
	Folder Name	STRING
	Domain	STRING
	Creator ID	STRING
	Parent Folder ID	STRING
	Created Time	TIMESTAMP
	Last Modified Time	TIMESTAMP
	Resource Type	STRING

3.1.10 builtin_userGroup Table

Table Name	Field Name	Field Type
builtin_userGroup	Domain	STRING
	User Group ID	STRING
	User Group Name	STRING
	Parent User Group ID	STRING
	Created Time	TIMESTAMP
	Last Modified Time	TIMESTAMP
	Custom Role	STRING

3.2 Built-in Dashboards

The current user behavior analysis module provides a set of general user behavior analysis visualization dashboard pages (page name: BI Platform User Behavior Analysis) based on the eight built-in datasets (see 3.1 Built-in Datasets), covering three standard analysis logics: system overview, page and card usage, and security monitoring.

In on-premises deployment environments, no user has permission to modify this built-in dashboard (not even administrators or owners), but the default administrator is the owner and can assign view/save-as permissions to other users. If enterprises need to customize their own user behavior analysis logic, they can perform secondary development based on the eight built-in datasets we provide.

3.2.1 System Overview

Page Module Name	Card Name	Card Description
System Overview	Number of System Users	Total number of current system users
	Number of User Groups	Total number of current system user groups
	Number of Pages	Total number of current system pages
	Number of Cards	Total number of current system cards
	Active Users	Total number of current active users
	ETL Run Count & Average Duration	Total number of ETL runs and average ETL task duration (in seconds)
	Top 10 Active Users	Top 10 active users in the current system
	Top 10 Active User Groups	Top 10 active user groups in the current system
	Pareto Analysis of High-frequency User Operations	Statistics of high-frequency operation types and counts of active users in the current system
	Peak Period Monitoring	Distribution of total visits by login method for each hour of each day in the current system
	API Calls and User Count Weekly Comparison in the Last 90 Days	Weekly comparison of API calls and user count changes in the last 90 days

3.2.2 Page and Card Usage

Page Module Name	Card Name	Card Description
Page and Card Usage	Most Popular Page Dashboards	Word cloud of the most popular page dashboard names in the current system
	New Cards and Card Creators Weekly Comparison in the Last 90 Days	Weekly comparison of new cards and card creators in the last 90 days
	User Group Card Access in the Last 30 Days	Changes in user group card access in the last 30 days
	User Group Card Access Count and Users in the Last 30 Days	Total user group card access count and users in the last 30 days

3.2.3 Security Monitoring

Page Module Name	Card Name	Card Description
Security Monitoring	User Export Behavior Monitoring	Daily monitoring of user export behavior, including who exported and what was exported
	User Delete Behavior Monitoring	Daily monitoring of user delete behavior, including who deleted and what was deleted

3.3 Built-in Task Operation Dashboard

To effectively simplify the work of IT operation and maintenance teams, Guanyuan Data has built a task operation dashboard in the BI platform, which visualizes all task operation information and allows quick location of problematic tasks when abnormalities are found.

To enable this feature, please contact technical support.

Instructions

• Built-in dataset: task_status table

• Dashboard: Task Analysis Dashboard, including common metrics such as daily task run count, average card run time, 90th percentile query time, and tasks with long CPU time.

3.4 Card Type Reference Table