Shulou(Shulou.com)11/24 Report--

With the advent of the digital age, the data exchange between enterprises and organizations is becoming more and more frequent and important. Different enterprises may have their own data resources, and these data resources may contain valuable information that can provide insight and decision support for other enterprises and organizations. However, because the data is stored in different database systems and based on the consideration of data security, the data analysis of inter-enterprise cooperation becomes complex and difficult.

System Overview in order to solve cross-enterprise data query, federated SQL has been developed, which allows users to query and analyze data sources across enterprises. It provides a simple and efficient way for cross-enterprise data query. It enables enterprises and organizations to easily share and access data and promotes cooperation and innovation. In addition, the Federal SQL also provides security and privacy protection mechanisms to ensure the security and privacy of data.

System introduction

1. Data resources: this module manages the data resources of the system, supports more than 20 heterogeneous data sources, and loads dynamic data sources. Provides data source configuration and SQL resource management functions. Members can authorize the use of the project after configuring the data resources available to the system.

two。 Resource authorization and permission configuration: the data resources added by the system can be authorized to the project, and members can use the data resources within the project for joint data analysis. For the sake of data security, members can control their own data resources.

Control methods include 1) the field "available" and select the fields that can be used in the sql statement. 2) Field "searchable", select the field that can be returned in the select clause. 3) the field "needs to be audited", and select the field that needs to be audited manually. 4) the field "minimum number of packets". In order to prevent the privacy of the group size from being too small, groups smaller than the specified size will not return data.

3. Project resource area: displays the authorized data resources within the project, and previews the data resources and meta-information.

4.SQL Discovery Editing area: our SQL Discovery page provides a convenient query interface for members to get results by entering query statements. In order to ensure the security and privacy of the data, we have made some restrictions and verification on the input query statements.

First of all, we are only allowed to enter query statements, not other types of SQL statements. This can prevent members from modifying or deleting the data and ensure the integrity and consistency of the data. At the same time, we restrict the use of only the fields available in the data permission configuration in the query statement. This prevents members from accessing data fields that they do not have permission to, and protects the security of the data.

Second, we are only allowed to query the fields that can be checked in the data permission configuration. This ensures that members can only query the data fields they have permissions to avoid access to and disclosure of sensitive data.

In addition, we restrict the group by field in the query statement. If the number of field groups for group by is less than the minimum number of groups set in the permission configuration, the query statement will not be allowed to execute. This can avoid the over-fine-grained grouping of the data and protect the privacy of the data.

Finally, our SQL discovery page supports the execution of multiple queries at the same time. This can improve the efficiency and flexibility of the query, and facilitate the members to carry out batch query and analysis.

In addition, on the SQL discovery page, we not only focus on the limitations of data security and query legitimacy, but also do a lot of optimization work to enhance the user experience. Association input: we have realized the function of SQL keyword association input. When the user enters keywords in the query sentence, the system will automatically prompt the possible keyword options to help the user quickly complete the writing of the query sentence. This can reduce the user's input errors and improve the accuracy of the query statement. We also realize the associative input function of resources. Regardless of member name, data source name, library name, table name or field name, when the user enters the relevant information in the query statement, the system will automatically prompt the possible options to help the user fill in quickly. Keyboard shortcuts: we also support keyboard shortcuts for general operations. For example, save, format, query, recall, cancel recall and other common operations. In this way, the operation efficiency and convenience of users are greatly improved.

5. Personal workspace: on the SQL exploration page, we provide users with a personal workspace, including note area, template, and function modules, in order to better support users' query and analysis needs.

Note area: users can save personal query statements as notes and browse SQL notes used by other users for reference and learning. This feature can help users better organize and manage personal queries, and can also draw inspiration and inspiration from the experience of other users.

Templates: we provide some system templates that contain references to some basic statements. Users can double-click the function name or statement to insert it at the cursor in the SQL editing area to quickly build the query statement. In addition, users can also customize their own templates to better adapt to personal query needs and workflow.

Function: the user can view the list of supported functions and double-click the function name to insert the function name at the cursor in the SQL editing area. This function is convenient for users to use and call various functions.

6. Results area: we not only provide rich query tools and functions, but also support multi-window results display and results download, as well as the ability to view execution history. Users can write multiple SQL statements in the SQL edit area and execute them. The query results of each statement are displayed in a separate window, making it easy for users to view multiple query results at the same time. This can not only improve the query efficiency, but also facilitate users to compare and analyze the results of different queries. Second, users can download the query results locally. We provide a download button so that users can choose to download the query results locally in CSV format to facilitate subsequent data analysis and processing.

Application scenario

Cross-organizational data query: when querying and analyzing data sets across different organizations or enterprises, federated SQL enables federated query and aggregation of data without centralizing data into a single location. For example, multiple banks in the financial industry can use Federal SQL to query customers' cross-bank transaction data for anti-money laundering analysis and risk assessment.

Multi-regional data analysis: when data is distributed in different regions or branches, federated SQL can be used to query and analyze on various data sources without centralizing the data in a central location. This is particularly useful in retail, logistics and other industries, such as cross-regional sales analysis, inventory management and other operations.

Data processing in a multi-cloud environment: federated SQL can query and federate operations between multiple cloud platforms or data centers without copying data to a central location. This is useful for enterprises that deploy applications or store data on multiple cloud platforms to enable data analysis and query across cloud platforms. Privacy protection data sharing: federal SQL can realize data sharing and query while protecting data privacy. For example, in the medical field, federal SQL can be used between different hospitals to query and analyze patient medical data without centralizing sensitive data in one location, thus protecting patient privacy.

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