QuickBI helps enterprises and individual users build data analysis systems through various data analysis and visualization capabilities. Using Quick BI to create beautiful dashboards, spreadsheets with complex formats, and download billions of data. Reports can be integrated into user's business processes and shared with colleagues and partners via email, DingTalk, corporate WeChat, etc.
Benefits
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Seamless Integration of Cloud Data
Supports multiple data sources, such as ApsaraDB for RDS, AnalyticDB, MaxCompute, MySQL, SQL Server, and local files.
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Quickly Builds Data Portals
Provides drag-and-drop operations, powerful data modeling, and data visualization to help you build data portals quickly.
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Flexible Embedding into Third-party Systems
You can embed the Quick BI dashboard into your own third-party systems and use it to view the reports and charts directly.
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Full Control of Data Access Permissions
You can set the access permissions for individual rows so that the same report is displayed differently for each user role.
Features
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Data sources
Connects to a wide range of data sources, including MaxCompute, RDS (for MySQL, PostgreSQL, and SQL Server), Analytic DB, HybridDB (for MySQL and PostgreSQL). Provides a standard interface for retrieving the metadata and data of data sources.
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Data modeling
Supports OLAP modeling of data sources, and converts data sources to multi-dimensional analytics models. Supports semantics such as dimensions (dates and locations), measures, star schema, and snowflake schema. Allows you to define calculated fields. The product allows you to edit the existing SQL script of the data source to customize your dimensions and measures.
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Dashboards
Enables users to build dashboards with visualization components. Supports 17 chart types, including line, pie, column, funnel, hierarchy, bubble geo, geo, and card. Also allows users to insert filter bars, TAB pages, iframe content, and text areas in the form of widgets as well as link multiple charts.
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Workbooks
Allows users to perform analytics in a spreadsheet environment. Supports row-based and column-based filters, basic and advanced filters, subtotals, auto-sum, and conditional formatting.
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Portals
Allows users to build portals from dashboards in a drag-and-drop manner. Supports embedded links (for dashboards), templates, and menu structures.
How it works
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Data Analysis and Effective Decision-making
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Access Control of Transaction Data
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Flexible Integration with Private Systems
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User Behavior Analysis
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Data-driven Marketing
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Analysis of Large Amounts of Marketing Data
Scenario One Qinsi Tech
Dynamic data analysis and effective decision-making
In data-driven business operations, we often need to create analysis reports based on data such as the customer retention rate and the number of active users. Quick BI is easy to use and provides multiple data presentation techniques that support dynamic data analysis and effective decision-making.
Challenges
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Difficult data extraction
For better decision-making, business managers often need to ask technical staff to write SQL statements in order to extract data based on different conditions.
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Inefficient reporting and high maintenance
The analysis system is difficult to develop and maintain, and generates reports with low efficiency.
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Poor visual design and high manpower costs
Reports that are created with tools such as HighChart have a poor visual design and require high manpower costs.
Scenario Two Shanghai Wosai Shouqianba
Access control of transaction data
All our managers need transaction data to measure the development of the business in different cities. It is vital that we find and locate any data exceptions as early as possible. Data access control is as important as data analysis.
Benefits
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Access permissions for individual rows
The same report is displayed differently for each user role. The Shanghai region manager can only view the data that is related to the Shanghai marketplace.
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Meets changing business needs
Statistical indicators constantly change with the growth of a business. When the server cannot handle all the requests, the server response slows down.
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Data integration across platforms and high computing performance
Quick BI supports data integration across multiple platforms and provides reliable computing performance for multi-dimensional analysis and data modeling.
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Scenario Three Qingju Tech Huochexiongdi
Flexible integration with private systems
The client wants to build a simple BI platform that supports data visualization and analysis at the lowest possible cost and in the shortest possible time. The platform also needs to integrate with the client's management system in order to provide data support for different staff in different regions.
Benefits
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Easy to use
The system is easy to use and user friendly, and meets the data needs of different staff.
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Improved data presentation
Supports integration with the internal system to perform data analysis, which significantly improves the efficiency of data visualization and analysis.
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An integrated system
Staff no longer need to switch between multiple systems.
Scenario Four Wangyuwangka
User behavior analysis
To better serve users, it is necessary to classify the users, identify user preferences, gather the operating conditions of the stores, and perform analysis on this data. The analysis results can be used to better predict user behavior.
Challenges
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User data extraction
How to gain insight from user behavioral data to provide better services.
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System construction costs
Traditional BI platforms and big data systems can be very expensive and slow to build.
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Collaboration between staff
It has always been a challenge to perform effective data analysis and reporting for a chain business. As most chain business staff are dispersed all over the country, it is difficult to provide business analysis reports and features to the staff.
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Scenario Five Nailist
Data-driven marketing towards millions of users
Nailist focuses on the e-commerce business and currently has millions of users. As Nailist has accumulated large amounts of user data, how to make better use of this data to improve the user experience is an important focus of Nailist's data exploration efforts.
Challenges
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Improve business insights
Improve business insights through effective business monitoring and data analysis.
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Business monitoring
Perform data-driven maketing towards millions of users and analyze user behavior in daily, weekly, monthly, and annual reports.
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How to adjust to changing business
To quickly evaluate the business performance requires fast data analysis and processing. Related Products and Services
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Scenario Six PING++
Analysis of large amounts of marketing data
Ping++ currently handles millions of transactions every day and has accumulated large amounts of transaction data. To improve the number of active users, Ping++ needs to perform effective data analysis and innovate. This requires a secure, reliable and stable big data platform.
Challenges
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How to be innovative
An end-to-end big data platform needs to support multiple features, such as storage, computing, business intelligence, and machine learning.
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How to be quick and cost-effective
As an Internet startup, the client needs to build the platform as quick as possible and at the lowest possible.
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How to be secure, stable, and reliable
To ensure that users can only access their own business data, a strong data protection mechanism is required.
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