技术领域Technical field
本发明涉及企业管理技术领域，具体是基于大数据分析的企业管理数据治理方法。The present invention relates to the technical field of enterprise management, specifically an enterprise management data governance method based on big data analysis.
背景技术Background technique
在企业的日常运营中，会产生大量的数据，包括业务数据、人员信息、财务数据等，企业管理数据治理是指涉及数据使用的一整套管理行为，由企业数据治理部门发起并推行，包括制定和实施针对整个企业内部数据的商业应用和技术管理的一系列流程，数据治理的目标是确保数据能够被准确地采集、存储、管理、共享和使用，从而支持企业组织的决策和业务需求；In the daily operations of an enterprise, a large amount of data will be generated, including business data, personnel information, financial data, etc. Enterprise management data governance refers to a set of management behaviors involving the use of data, which is initiated and implemented by the enterprise data governance department, including formulating and implement a series of processes for business applications and technical management of data within the entire enterprise. The goal of data governance is to ensure that data can be accurately collected, stored, managed, shared and used to support the decision-making and business needs of the enterprise organization;
目前针对企业管理数据的治理面临着诸多挑战，如数据的准确性和完整性、数据安全和隐私保护、数据共享和利用等问题，还存在流程不规范、权限不明确、数据质量不高等问题，难以满足现代企业的需求，以及无法在发现问题和风险时进行预警信息的显示亮度自动合理调控，并在显示区域无人时自动选定最适管理人员并向其发送预警管理通知，不利于及时进行相应改善措施；Currently, the governance of enterprise management data faces many challenges, such as data accuracy and completeness, data security and privacy protection, data sharing and utilization, etc. There are also problems such as irregular processes, unclear permissions, and low data quality. It is difficult to meet the needs of modern enterprises, and it is unable to automatically and reasonably adjust the display brightness of early warning information when problems and risks are discovered, and automatically select the most suitable managers when there is no one in the display area and send them early warning management notifications, which is not conducive to timely Carry out corresponding improvement measures;
针对上述的技术缺陷，现提出一种解决方案。In view of the above technical defects, a solution is proposed.
发明内容Contents of the invention
本发明的目的在于提供基于大数据分析的企业管理数据治理方法，解决了现有技术存在流程不规范、权限不明确、数据质量不高等问题，难以满足现代企业的需求，以及无法在发现问题和风险时进行预警信息的显示亮度自动合理调控，并在显示区域无人时自动选定最适管理人员并向其发送预警管理通知，不利于及时进行相应改善措施的问题。The purpose of the present invention is to provide an enterprise management data governance method based on big data analysis, which solves the problems in the existing technology such as non-standardized processes, unclear authority, low data quality, etc., making it difficult to meet the needs of modern enterprises, and being unable to detect problems and Automatically and reasonably adjust the display brightness of early warning information when there is a risk, and automatically select the most appropriate manager when there is no one in the display area and send early warning management notifications to them, which is not conducive to timely implementation of corresponding improvement measures.
为实现上述目的，本发明提供如下技术方案：In order to achieve the above objects, the present invention provides the following technical solutions:
基于大数据分析的企业管理数据治理方法，包括以下步骤：The enterprise management data governance method based on big data analysis includes the following steps:
步骤一、建立企业数据治理框架：确定数据所有者，制定数据管理和操作规范，且确定数据安全和隐私保护措施，并确定数据共享和利用规则，以及制定数据质量管理、校验规则和确定数据生命周期管理策略；Step 1. Establish an enterprise data governance framework: identify data owners, formulate data management and operating specifications, determine data security and privacy protection measures, determine data sharing and utilization rules, and formulate data quality management, verification rules and determine data life cycle management strategy;
步骤二、数据质量管理：采取数据清洗、校验和规范化的操作，确保数据的准确性、一致性、完整性和可靠性；Step 2. Data quality management: adopt data cleaning, verification and standardization operations to ensure the accuracy, consistency, completeness and reliability of the data;
步骤三、数据安全管理：采取数据加密、访问控制和审计的措施，保护数据的隐私和安全；Step 3. Data security management: Take data encryption, access control and audit measures to protect the privacy and security of data;
步骤四、数据生命周期管理：管理数据的创建、存储、传输、共享和销毁环节，确保数据的有效利用和合规处理；Step 4. Data life cycle management: manage the creation, storage, transmission, sharing and destruction of data to ensure the effective utilization and compliance processing of data;
步骤五、监控和优化：对数据治理过程进行监控和优化，及时发现和解决数据治理问题，提高数据治理效率和质量。Step 5. Monitor and optimize: Monitor and optimize the data governance process, discover and solve data governance problems in a timely manner, and improve data governance efficiency and quality.
进一步的，步骤一中，在确定数据的所有者时，包括确定数据的创建者、拥有者、管理者和访问者，以及明确数据所有者的职责和权限，确保数据的统一管理和控制；在制定数据管理和操作规范时，根据企业的业务需求和数据管理要求，制定数据管理和操作规范，包括数据的格式、标准、存储方式、传输规则和访问控制；在确定数据安全和隐私保护措施时，包括数据加密、访问控制、身份认证、数据备份和恢复措施，以确保数据的安全和隐私保护；Furthermore, in step one, when determining the owner of the data, it includes determining the creator, owner, manager and visitor of the data, as well as clarifying the responsibilities and permissions of the data owner to ensure unified management and control of the data; in When formulating data management and operation specifications, formulate data management and operation specifications based on the business needs and data management requirements of the enterprise, including data format, standards, storage methods, transmission rules and access control; when determining data security and privacy protection measures , including data encryption, access control, identity authentication, data backup and recovery measures to ensure data security and privacy protection;
在确定数据共享和利用规则时，包括数据的共享范围、目的、方式和使用期限，以确保数据的合理利用和保护；在制定数据质量管理和校验规则时，包括数据完整性、准确性和一致性的要求，以及数据校验和修正的流程和方法，通过制定规范和规则以确保数据的准确性和可靠性；在确定数据生命周期管理策略时，包括数据的创建、存储、传输、共享和销毁环节的管理要求和操作流程，以确保数据的合理利用和及时处理。When determining data sharing and utilization rules, include the data sharing scope, purpose, method and usage period to ensure the reasonable utilization and protection of data; when formulating data quality management and verification rules, include data integrity, accuracy and Consistency requirements, as well as data verification and correction processes and methods, ensure the accuracy and reliability of data by formulating specifications and rules; when determining data life cycle management strategies, including data creation, storage, transmission, and sharing and management requirements and operating procedures for the destruction process to ensure the reasonable utilization and timely processing of data.
进一步的，在步骤二中，数据清洗是数据预处理的过程以去除数据中的噪声和冗余信息，使数据符合后续处理的要求，数据清洗的具体步骤包括去除空值、填充缺失值、处理异常值和去除重复数据；数据校验是验证数据准确性、一致性和完整性的过程，通过数据校验以发现数据中的错误、不一致和缺失问题，并进行相应的处理和修正，数据校验的具体方法包括数据范围检查、规则检查、关系检查和一致性检查；数据规范化是将数据按照一定的标准进行转换和调整，使其符合后续处理的要求，具体方法包括数据标准化、归一化、离散化和编码，通过数据规范化以提高数据的可比性和可操作性。Furthermore, in step two, data cleaning is a process of data preprocessing to remove noise and redundant information in the data so that the data meets the requirements of subsequent processing. The specific steps of data cleaning include removing null values, filling missing values, and processing Outliers and removal of duplicate data; data verification is the process of verifying the accuracy, consistency and completeness of data. Through data verification, errors, inconsistencies and missing problems in the data are discovered, and corresponding processing and correction are carried out. Data verification The specific methods of verification include data range check, rule check, relationship check and consistency check; data normalization is to convert and adjust the data according to certain standards to make it meet the requirements of subsequent processing. Specific methods include data standardization and normalization. , discretization and coding, and data standardization to improve data comparability and operability.
进一步的，在步骤三中，数据加密是通过加密算法将数据进行加密处理，使数据变为无法读取或理解的密文，在数据传输和存储过程中，加密以防止数据被非法获取和窃取，所采用的加密技术包括对称加密和非对称加密；访问控制是对数据访问权限的控制，只有具有相应权限的用户才能访问和操作数据，所制定的访问控制策略包括基于角色的访问控制和基于属性的访问控制，以限制数据的访问权限和防止非法访问、数据泄露；审计是对数据安全管理的监督和检查，以发现和纠正数据安全管理中存在的问题和风险，所建立的审计机制包括数据安全审计和安全事件审计。Further, in step three, data encryption is to encrypt the data through an encryption algorithm, turning the data into ciphertext that cannot be read or understood. During the data transmission and storage process, encryption is performed to prevent the data from being illegally obtained and stolen. , the encryption technology used includes symmetric encryption and asymmetric encryption; access control is the control of data access permissions. Only users with corresponding permissions can access and operate data. The developed access control policies include role-based access control and Access control of attributes to limit data access rights and prevent illegal access and data leakage; auditing is the supervision and inspection of data security management to discover and correct problems and risks in data security management. The audit mechanism established includes Data security audit and security incident audit.
进一步的，在步骤四中，数据创建是数据的录入、生成或采集过程，通过制定数据创建的标准和流程，确保数据的准确性和完整性；数据存储是数据的保存和管理过程，通过选择合适的存储介质和存储方式，确保数据的安全和可用性；数据传输是数据在不同系统或节点之间的传输过程，通过建立数据传输的通道和规则，确保数据传输的可靠性和安全性；数据共享是数据向外部机构或个人的共享过程，通过制定数据共享的规则和流程，确保数据的合理利用和保护；数据销毁是数据的删除和销毁过程，通过建立数据销毁的流程和标准，确保数据的彻底删除和隐私保护。Further, in step four, data creation is the process of data entry, generation or collection. The accuracy and integrity of data are ensured by formulating standards and processes for data creation; data storage is the process of data preservation and management. By selecting Appropriate storage media and storage methods ensure the security and availability of data; data transmission is the transmission process of data between different systems or nodes. The reliability and security of data transmission are ensured by establishing data transmission channels and rules; data Sharing is the process of sharing data to external organizations or individuals. By formulating rules and processes for data sharing, the reasonable utilization and protection of data are ensured; data destruction is the process of deleting and destroying data. By establishing processes and standards for data destruction, ensuring data Complete deletion and privacy protection.
进一步的，步骤五的具体操作过程如下：Further, the specific operation process of step five is as follows:
建立监控体系：建立数据治理过程的监控体系，包括对数据质量、数据安全和数据生命周期的监控，通过监控体系以实时检测数据治理问题的出现和变化情况；设立指标和标准：设立数据治理的指标和标准，用于评估数据治理的效果和质量，指标和标准具有可衡量性和可比较性，以在实际操作中能够准确评估数据治理的水平；Establish a monitoring system: Establish a monitoring system for the data governance process, including monitoring of data quality, data security and data life cycle. Through the monitoring system, the emergence and changes of data governance issues can be detected in real time; Establish indicators and standards: Establish data governance Indicators and standards are used to evaluate the effectiveness and quality of data governance. The indicators and standards are measurable and comparable to accurately assess the level of data governance in actual operations;
进行分析和诊断：对监控数据进行分析和诊断，找出数据治理中存在的问题和风险，通过对比指标和标准，发现数据治理的不足和需要改进的方面；实施优化措施：根据分析和诊断结果，实施针对性的优化措施，优化措施包括改进数据治理流程、完善数据规范和加强数据安全防护；定期评估和调整：定期评估数据治理的效果和质量，对优化措施进行定期调整和改进，通过不断优化和调整以提高数据治理的水平和服务质量。Analyze and diagnose: Analyze and diagnose monitoring data to identify problems and risks in data governance. By comparing indicators and standards, discover deficiencies in data governance and areas that need improvement; implement optimization measures: based on analysis and diagnosis results , implement targeted optimization measures, which include improving data governance processes, improving data specifications, and strengthening data security protection; regular assessment and adjustment: Regularly assess the effect and quality of data governance, regularly adjust and improve optimization measures, and continuously Optimize and adjust to improve the level of data governance and service quality.
进一步的，企业管理数据治理通过数据治理平台实现，数据治理平台在进行监控和优化时基于数据治理中存在的问题和风险生成对应的预警信息，将对应预警信息发送至可视化操作模块进行信息显示预警；可视化操作模块在进行信息显示预警时通过显示区域实时监控以判断显示区域是否存在管理人员，若显示区域存在管理人员，则通过预显检测分析以进行亮度自动调控；若显示区域不存在管理人员，则生成预警推送分析信号并将其发送至数据治理平台，数据治理平台接收到预警推送分析信号时进行预警推送分析以确定最优管理人员，并将相应预警信息发送至最优管理人员的智能终端。Furthermore, enterprise management data governance is realized through the data governance platform. When monitoring and optimizing, the data governance platform generates corresponding early warning information based on the problems and risks existing in data governance, and sends the corresponding early warning information to the visual operation module for information display and early warning. ; When performing information display warning, the visual operation module monitors the display area in real time to determine whether there is a manager in the display area. If there is a manager in the display area, it will automatically adjust the brightness through pre-display detection and analysis; if there is no manager in the display area , an early warning push analysis signal is generated and sent to the data governance platform. When the data governance platform receives the early warning push analysis signal, it performs early warning push analysis to determine the optimal manager, and sends the corresponding early warning information to the intelligence of the optimal manager. terminal.
进一步的，预显检测分析的具体分析过程如下：Further, the specific analysis process of pre-display detection analysis is as follows:
通过分析获取到视况值和显表值，将视况值和显表值与预设视况阈值和预设显表阈值分别进行数值比较，若视况值和显表值均超过对应预设阈值，则生成高亮度显示信号，若视况值和显表值均未超过对应预设阈值，则生成低亮度显示信号，其余情况则生成中亮度显示信号；事先设定高亮度显示信号、中亮度显示信号和低亮度显示信号分别对应一组亮度显示范围，可视化操作模块基于所生成的亮度显示信号确定相适配的亮度显示范围，若可视化操作模块的实际亮度处于相适配的亮度显示范围内，则不进行亮度调控，否则自动将显示亮度调节至相适配的亮度显示范围内。Obtain the visual status value and the display meter value through analysis, and compare the visual status value and the display meter value with the preset visual status threshold and the preset display meter threshold respectively. If both the visual status value and the display meter value exceed the corresponding preset threshold, a high-brightness display signal is generated. If neither the visual value nor the display value exceeds the corresponding preset threshold, a low-brightness display signal is generated. In other cases, a medium-brightness display signal is generated; set the high-brightness display signal, medium-brightness display signal in advance The brightness display signal and the low brightness display signal respectively correspond to a set of brightness display ranges. The visual operation module determines the matching brightness display range based on the generated brightness display signal. If the actual brightness of the visual operation module is within the matching brightness display range within, no brightness adjustment is performed, otherwise the display brightness will be automatically adjusted to the appropriate brightness display range.
进一步的，通过分析获取到视况值和显表值的具体过程如下：Further, the specific process of obtaining the visual value and display value through analysis is as follows:
采集到显示区域中所有管理人员的人员位置，将可视化操作模块的中心点与对应人员位置进行距离计算得到人机距离值，以可视化操作模块的中心点为端点向其正前方画垂直于可视化操作模块的射线并标记为前延垂直射线，将可视化操作模块的中点与对应人员位置进行连线并将该线段标记为人机路径线段；将对应人员的人机路径线段与前延垂直射线之间的夹角标记为视线斜角值；Collect the personnel positions of all managers in the display area, calculate the distance between the center point of the visual operation module and the corresponding personnel position to obtain the human-machine distance value, and use the center point of the visual operation module as the endpoint to draw a line perpendicular to the visual operation directly in front of it. The ray of the module is marked as a forward vertical ray. Connect the midpoint of the visual operation module with the position of the corresponding person and mark the line segment as a human-machine path segment; connect the corresponding human-machine path line segment with the forward vertical ray. The angle mark is the line of sight oblique angle value;
将视线斜角值与人机距离值进行分析计算得到视晰值，将所有管理人员的视晰值建立集合，将集合中数值最大的子集标记为视晰上限值，将集合中的所有子集进行均值计算得到视晰平均值，将视晰上限值和视晰平均值进行分析计算得到视况值；以及在可视化操作模块的显示面设定若干个温测点，实时采集温测点的温度值，将所有温度值进行求和计算并取均值得到显温值，并采集到显示区域的环境温度数据、环境亮度数据和粉尘浓度数据，将显温值、环境温度数据、环境亮度数据和粉尘浓度数据进行归一化计算得到显表值。Analyze and calculate the sight angle value and the human-machine distance value to obtain the visual clarity value. Create a set of the visual clarity values of all managers. Mark the subset with the largest value in the set as the visual clarity upper limit value. All the visual clarity values in the set are The subset is averaged to obtain the average visual clarity, and the upper limit of visual clarity and the average visual clarity are analyzed and calculated to obtain the visual status value; and several temperature measurement points are set on the display surface of the visual operation module to collect temperature measurements in real time The temperature value of the point is calculated by summing all the temperature values and taking the average value to obtain the displayed temperature value. The ambient temperature data, ambient brightness data and dust concentration data of the display area are collected. The displayed temperature value, ambient temperature data and ambient brightness data are collected. The data and dust concentration data are normalized and calculated to obtain the apparent value.
进一步的，预警推送分析的具体分析过程如下：Further, the specific analysis process of early warning push analysis is as follows:
获取到所有管理人员的智能终端信息，向所有管理人员发送预警指令并接收到管理人员的确认指令，将在规定时间内回复确认指令的管理人员标记为待选对象；采集到对应待选对象的管理时长，以及采集到待选对象处理对应预警操作的出发准备时长平均值以及延迟到达占比值，且获取到每次延迟到达的延迟时长，将所有延迟时长进行求和计算并取均值得到延时分析值；Obtain the smart terminal information of all managers, send early warning instructions to all managers and receive confirmation instructions from managers, and mark managers who reply to the confirmation instructions within the specified time as candidates for selection; collect the information of the corresponding candidates The management time is collected, and the average departure preparation time and delayed arrival ratio of the corresponding warning operation of the candidate object processing are collected, and the delay time of each delayed arrival is obtained, and all delay times are summed and calculated and the average value is obtained to obtain the delay analysis value;
将管理时长、出发准备时长平均值、延迟到达占比值和延时分析值进行数值计算得到推析值，将推析值与预设推析阈值进行数值比较，若推析值超过预设推析阈值，则将对应待选对象标记为可选对象；采集到可选对象与可视化操作模块之间的路径距离并标记为前行距离值，按照前行距离值的数值由大到小将所有可选对象进行排序，将位于最后一位的可选对象标记为最优管理人员。Calculate the management time, the average departure preparation time, the delay arrival ratio and the delay analysis value to obtain the inference value. Compare the inference value with the preset inference threshold. If the inference value exceeds the preset inference value, threshold, mark the corresponding object to be selected as an optional object; collect the path distance between the optional object and the visual operation module and mark it as a forward distance value, and all selectable objects will be classified according to the value of the forward distance value from large to small. The objects are sorted and the last selectable object is marked as the best manager.
与现有技术相比，本发明的有益效果是：Compared with the prior art, the beneficial effects of the present invention are:
1、本发明中，通过建立企业数据治理框架、数据质量管理、数据安全管理、数据生命周期管理以及监控和优化，基于规范数据管理和操作流程，提高了数据的准确性和完整性，保护了数据的隐私和安全，实现了数据的优化和规范管理，能够应对目前对企业管理数据的管理所面临的诸多挑战，解决了目前企业数据管理中所存在的流程不规范、权限不明确、数据质量不高等问题，有助于满足现代企业的需求；1. In the present invention, by establishing an enterprise data governance framework, data quality management, data security management, data life cycle management, monitoring and optimization, and based on standardizing data management and operating procedures, the accuracy and integrity of data are improved, and the data is protected. The privacy and security of data realize the optimization and standardized management of data, which can meet the many challenges faced by the current management of enterprise data and solve the problems of irregular processes, unclear permissions and data quality in current enterprise data management. Not high-level issues, helping to meet the needs of modern enterprises;
2、本发明中，在进行监控和优化时基于数据治理中存在的问题和风险生成对应的预警信息，将对应预警信息发送至可视化操作模块进行信息显示预警，若显示区域存在管理人员则通过预显检测分析以进行亮度自动调控，能够在发现问题和风险时进行预警信息的显示亮度自动合理调控，有助于显示区域所有管理人员看清预警显示内容；以及在显示区域不存在管理人员时通过预警推送分析以确定最优管理人员，有利于及时进行相应改善措施，进一步提升其智能化程度。2. In the present invention, when monitoring and optimizing, corresponding early warning information is generated based on the problems and risks existing in data governance, and the corresponding early warning information is sent to the visual operation module for information display and early warning. If there are managers in the display area, the warning information is generated through the early warning information. Display detection analysis is used to automatically adjust the brightness, which can automatically and reasonably adjust the display brightness of early warning information when problems and risks are discovered, helping all managers in the display area to clearly see the early warning display content; and when there are no managers in the display area, Early warning push analysis to determine the optimal management personnel is conducive to timely implementation of corresponding improvement measures and further enhances its intelligence.
附图说明Description of the drawings
为了便于本领域技术人员理解，下面结合附图对本发明作进一步的说明；In order to facilitate understanding by those skilled in the art, the present invention will be further described below in conjunction with the accompanying drawings;
图1为本发明的方法流程图。Figure 1 is a flow chart of the method of the present invention.
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.
实施例一：如图1所示，本发明提出的基于大数据分析的企业管理数据治理方法，包括以下步骤：Embodiment 1: As shown in Figure 1, the enterprise management data governance method based on big data analysis proposed by the present invention includes the following steps:
步骤一、建立企业数据治理框架：确定数据所有者，制定数据管理和操作规范，且确定数据安全和隐私保护措施，并确定数据共享和利用规则，以及制定数据质量管理、校验规则和确定数据生命周期管理策略；Step 1. Establish an enterprise data governance framework: identify data owners, formulate data management and operating specifications, determine data security and privacy protection measures, determine data sharing and utilization rules, and formulate data quality management, verification rules and determine data life cycle management strategy;
具体而言，确定数据的所有者：首先需要确定数据的所有者，包括数据的创建者、拥有者、管理者和访问者等，明确数据所有者的职责和权限，确保数据的统一管理和控制；制定数据管理和操作规范：根据企业的业务需求和数据管理要求，制定数据管理和操作规范。包括数据的格式、标准、存储方式、传输规则、访问控制等方面。规范应尽量详细、明确，以便实际操作时能够准确执行；确定数据安全和隐私保护措施：在数据治理框架中，需要明确数据安全和隐私保护的措施，包括数据加密、访问控制、身份认证、数据备份和恢复等措施，以确保数据的安全和隐私保护；Specifically, determine the owner of the data: First, you need to determine the owner of the data, including the creator, owner, manager, and visitor of the data, clarify the responsibilities and permissions of the data owner, and ensure unified management and control of the data. ; Develop data management and operating specifications: Develop data management and operating specifications based on the business needs and data management requirements of the enterprise. Including data format, standards, storage methods, transmission rules, access control, etc. Specifications should be as detailed and clear as possible so that they can be accurately implemented in actual operations; determine data security and privacy protection measures: In the data governance framework, data security and privacy protection measures need to be clarified, including data encryption, access control, identity authentication, data Measures such as backup and recovery to ensure data security and privacy protection;
确定数据共享和利用规则：企业通常需要与外部机构或个人进行数据共享，因此需要制定数据共享和利用规则。包括数据的共享范围、目的、方式、使用期限等方面，以确保数据的合理利用和保护；制定数据质量管理和校验规则：数据治理框架中需要包含数据质量管理和校验规则。包括数据完整性、准确性、一致性等方面的要求，以及数据校验和修正的流程和方法。通过制定规范和规则，确保数据的准确性和可靠性；确定数据生命周期管理策略：数据在不同阶段具有不同的价值和使用方式，因此需要制定数据生命周期管理策略，包括数据的创建、存储、传输、共享和销毁等环节的管理要求和操作流程，以确保数据的合理利用和及时处理；Determine data sharing and utilization rules: Enterprises often need to share data with external organizations or individuals, so they need to establish data sharing and utilization rules. Including the sharing scope, purpose, method, usage period, etc. of data to ensure the reasonable utilization and protection of data; formulate data quality management and verification rules: the data governance framework needs to include data quality management and verification rules. Including requirements for data integrity, accuracy, consistency, etc., as well as processes and methods for data verification and correction. Ensure the accuracy and reliability of data by formulating specifications and rules; determine data life cycle management strategies: Data has different values and usage patterns at different stages, so it is necessary to formulate data life cycle management strategies, including data creation, storage, Management requirements and operating procedures for transmission, sharing, and destruction to ensure reasonable utilization and timely processing of data;
步骤二、数据质量管理：采取数据清洗、校验和规范化的操作，确保数据的准确性、一致性、完整性和可靠性，提高数据的质量和价值；Step 2. Data quality management: adopt data cleaning, verification and standardization operations to ensure the accuracy, consistency, integrity and reliability of the data and improve the quality and value of the data;
具体而言，数据清洗是数据预处理的过程以去除数据中的噪声和冗余信息，使数据符合后续处理的要求，数据清洗的具体步骤包括去除空值、填充缺失值、处理异常值和去除重复数据等；数据校验是验证数据准确性、一致性和完整性的过程，通过数据校验以发现数据中的错误、不一致和缺失问题，并进行相应的处理和修正，数据校验的具体方法包括数据范围检查、规则检查、关系检查和一致性检查等；数据规范化是将数据按照一定的标准进行转换和调整，使其符合后续处理的要求，具体方法包括数据标准化、归一化、离散化和编码等，通过数据规范化以提高数据的可比性和可操作性；Specifically, data cleaning is the process of data preprocessing to remove noise and redundant information in the data so that the data meets the requirements of subsequent processing. The specific steps of data cleaning include removing null values, filling missing values, processing outliers and removing Duplicate data, etc.; data verification is the process of verifying the accuracy, consistency and completeness of data. Through data verification, errors, inconsistencies and missing problems in the data are discovered, and corresponding processing and correction are carried out. The specific details of data verification are Methods include data range check, rule check, relationship check, consistency check, etc.; data normalization is to convert and adjust the data according to certain standards to make it meet the requirements of subsequent processing. Specific methods include data standardization, normalization, discrete ization and coding, etc., to improve the comparability and operability of data through data standardization;
步骤三、数据安全管理：采取数据加密、访问控制和审计的措施，保护数据的隐私和安全，防止数据被非法获取、泄露和滥用；Step 3. Data security management: Take data encryption, access control and audit measures to protect the privacy and security of data and prevent data from being illegally obtained, leaked and abused;
具体而言，数据加密是通过加密算法将数据进行加密处理，使数据变为无法读取或理解的密文，在数据传输和存储过程中，加密以防止数据被非法获取和窃取，企业数据管理可以采用多种加密技术，如对称加密、非对称加密等，以保护数据的隐私和安全；访问控制是对数据访问权限的控制，只有具有相应权限的用户才能访问和操作数据，企业通过制定访问控制策略，包括基于角色的访问控制、基于属性的访问控制等，以限制数据的访问权限，防止非法访问和数据泄露；审计是对数据安全管理的监督和检查，旨在发现和纠正数据安全管理中存在的问题和风险，企业通过建立审计机制，包括数据安全审计、安全事件审计等，及时发现和解决数据安全问题，提高数据的安全性和可靠性；Specifically, data encryption is to encrypt data through encryption algorithms, turning the data into ciphertext that cannot be read or understood. During the data transmission and storage process, encryption is used to prevent data from being illegally obtained and stolen. Enterprise data management A variety of encryption technologies can be used, such as symmetric encryption, asymmetric encryption, etc., to protect the privacy and security of data; access control is the control of data access permissions. Only users with corresponding permissions can access and operate data. Enterprises can set access requirements by formulating Control strategies, including role-based access control, attribute-based access control, etc., to limit data access rights and prevent illegal access and data leakage; auditing is the supervision and inspection of data security management, aiming to discover and correct data security management To solve existing problems and risks, enterprises can promptly discover and solve data security problems and improve data security and reliability by establishing audit mechanisms, including data security audits, security incident audits, etc.;
步骤四、数据生命周期管理：管理数据的创建、存储、传输、共享和销毁环节，确保数据的有效利用和合规处理，避免数据泄露、滥用和丢失等风险；Step 4. Data life cycle management: Manage the creation, storage, transmission, sharing and destruction of data to ensure the effective use and compliance processing of data and avoid risks such as data leakage, abuse and loss;
具体而言，数据创建是数据的录入、生成或采集过程，通过制定数据创建的标准和流程，确保数据的准确性和完整性；数据存储是数据的保存和管理过程，通过选择合适的存储介质和存储方式，确保数据的安全和可用性；数据传输是数据在不同系统或节点之间的传输过程，通过建立数据传输的通道和规则，确保数据传输的可靠性和安全性；数据共享是数据向外部机构或个人的共享过程，通过制定数据共享的规则和流程，确保数据的合理利用和保护；数据销毁是数据的删除和销毁过程，通过建立数据销毁的流程和标准，确保数据的彻底删除和隐私保护；Specifically, data creation is the process of data entry, generation or collection. By formulating standards and processes for data creation, the accuracy and integrity of data are ensured; data storage is the process of data preservation and management, by selecting appropriate storage media. and storage methods to ensure the security and availability of data; data transmission is the transmission process of data between different systems or nodes, and the reliability and security of data transmission are ensured by establishing data transmission channels and rules; data sharing is the process of data transmission to The sharing process of external organizations or individuals ensures the reasonable use and protection of data by formulating rules and procedures for data sharing; data destruction is the deletion and destruction process of data, and ensures the complete deletion and destruction of data by establishing data destruction processes and standards. privacy protection;
步骤五、监控和优化：对数据治理过程进行监控和优化，及时发现和解决数据治理问题，提高数据治理效率和质量，实现数据的优化和规范管理；具体操作过程如下：Step 5. Monitor and optimize: Monitor and optimize the data governance process, discover and solve data governance problems in a timely manner, improve data governance efficiency and quality, and achieve data optimization and standardized management; the specific operation process is as follows:
建立监控体系：建立数据治理过程的监控体系，包括对数据质量、数据安全和数据生命周期的监控，通过监控体系以实时检测数据治理问题的出现和变化情况；设立指标和标准：设立数据治理的指标和标准，用于评估数据治理的效果和质量，指标和标准具有可衡量性和可比较性，以在实际操作中能够准确评估数据治理的水平；Establish a monitoring system: Establish a monitoring system for the data governance process, including monitoring of data quality, data security and data life cycle. Through the monitoring system, the emergence and changes of data governance issues can be detected in real time; Establish indicators and standards: Establish data governance Indicators and standards are used to evaluate the effectiveness and quality of data governance. The indicators and standards are measurable and comparable to accurately assess the level of data governance in actual operations;
进行分析和诊断：对监控数据进行分析和诊断，找出数据治理中存在的问题和风险，通过对比指标和标准，发现数据治理的不足和需要改进的方面；实施优化措施：根据分析和诊断结果，实施针对性的优化措施，优化措施包括改进数据治理流程、完善数据规范和加强数据安全防护；定期评估和调整：定期评估数据治理的效果和质量，对优化措施进行定期调整和改进，通过不断优化和调整以提高数据治理的水平和服务质量。Analyze and diagnose: Analyze and diagnose monitoring data to identify problems and risks in data governance. By comparing indicators and standards, discover deficiencies in data governance and areas that need improvement; implement optimization measures: based on analysis and diagnosis results , implement targeted optimization measures, which include improving data governance processes, improving data specifications, and strengthening data security protection; regular assessment and adjustment: Regularly assess the effect and quality of data governance, regularly adjust and improve optimization measures, and continuously Optimize and adjust to improve the level of data governance and service quality.
通过上述企业管理数据治理方法，基于规范数据管理和操作流程，提高了数据的准确性和完整性，保护了数据的隐私和安全，实现了数据的优化和规范管理，能够应对目前对企业管理数据的管理所面临的诸多挑战，如数据的准确性和完整性、数据安全和隐私保护、数据共享和利用等问题，解决了目前企业数据管理中所存在的流程不规范、权限不明确、数据质量不高等问题，有助于满足现代企业的需求。Through the above enterprise management data governance method, based on standardized data management and operating procedures, the accuracy and integrity of data are improved, the privacy and security of data are protected, the optimization and standardized management of data are realized, and the current demand for enterprise management data can be dealt with. Management faces many challenges, such as data accuracy and completeness, data security and privacy protection, data sharing and utilization, etc. It solves the current irregular processes, unclear permissions, and data quality existing in enterprise data management. Not high-level questions, helping to meet the needs of modern enterprises.
实施例二：本实施例与实施例1的区别在于，企业管理数据治理通过数据治理平台实现，数据治理平台在进行监控和优化时基于数据治理中存在的问题和风险生成对应的预警信息，将对应预警信息发送至可视化操作模块进行信息显示预警；可视化操作模块在进行信息显示预警时通过显示区域实时监控以判断显示区域是否存在管理人员，若显示区域存在管理人员，则通过预显检测分析以进行亮度自动调控，能够在发现问题和风险时进行预警信息的显示亮度自动合理调控，有助于显示区域所有管理人员看清预警显示内容，智能化程度高；预显检测分析的具体分析过程如下：Embodiment 2: The difference between this embodiment and Embodiment 1 is that enterprise management data governance is implemented through a data governance platform. When monitoring and optimizing, the data governance platform generates corresponding early warning information based on the problems and risks existing in data governance, and The corresponding early warning information is sent to the visual operation module for information display and early warning; when the visual operation module performs information display and early warning, it monitors the display area in real time to determine whether there are managers in the display area. If there are managers in the display area, it uses pre-display detection and analysis to Automatic brightness adjustment can automatically and reasonably adjust the display brightness of early warning information when problems and risks are discovered, which helps all managers in the display area to see the early warning display content clearly, with a high degree of intelligence; the specific analysis process of pre-display detection analysis is as follows :
通过分析获取到视况值和显表值，具体为：采集到显示区域中所有管理人员的人员位置，将可视化操作模块的中心点与对应人员位置进行距离计算得到人机距离值QT，以可视化操作模块的中心点为端点向其正前方画垂直于可视化操作模块的射线并标记为前延垂直射线，将可视化操作模块的中点与对应人员位置进行连线并将该线段标记为人机路径线段；将对应人员的人机路径线段与前延垂直射线之间的夹角标记为视线斜角值SX；其中，需要说明的是，对应管理人员的人机距离值QT的数值越大，视线斜角值SX的数值越大，则对应管理人员越难看清显示内容，越需要适当提高显示亮度；The visual value and display value are obtained through analysis, specifically: the personnel positions of all managers in the display area are collected, and the distance between the center point of the visual operation module and the corresponding personnel position is calculated to obtain the human-machine distance value QT to visualize The center point of the operation module is the endpoint. Draw a ray perpendicular to the visual operation module directly in front of it and mark it as a forward vertical ray. Connect the midpoint of the visual operation module with the corresponding personnel position and mark this line segment as a human-machine path segment. ; Mark the angle between the human-machine path line segment of the corresponding person and the forward vertical ray as the line of sight slant angle value SX; where, it should be noted that the greater the value of the human-machine distance value QT of the corresponding manager, the slant of the line of sight The larger the angle value SX, the harder it is for managers to see the display content clearly, and the more the display brightness needs to be appropriately increased;
通过公式QS=kq1*SX+kq2*QT将视线斜角值SX与人机距离值QT进行分析计算得到视晰值QS，其中，kq1、kq2为预设权重系数，且kq1＞kq2＞0；并且，视晰值QS的数值越大，表明对应管理人员越难看清显示内容；将所有管理人员的视晰值建立集合，将集合中数值最大的子集标记为视晰上限值，将集合中的所有子集进行均值计算得到视晰平均值，通过公式QK=（kq3*SF1+kq4*SF2）/2将视晰上限值SF1和视晰平均值SF2进行分析计算得到视况值QK；其中，kq3、kq4为预设比例系数，且kq4＞kq3＞0；并且，视况值QK的数值越大，表明整体而言所有管理人员越难以看清预警显示内容；The visual clarity value QS is obtained by analyzing and calculating the line of sight oblique angle value SX and the human-machine distance value QT through the formula QS=kq1*SX+kq2*QT, where kq1 and kq2 are preset weight coefficients, and kq1>kq2>0; Moreover, the larger the value of the visual clarity value QS, the harder it is for the corresponding manager to see the displayed content; a set is established for the visual clarity values of all managers, and the subset with the largest value in the set is marked as the visual clarity upper limit value, and the set is All subsets in are averaged to obtain the visual clarity average value. The visual clarity upper limit value SF1 and the visual clarity average value SF2 are analyzed and calculated using the formula QK=(kq3*SF1+kq4*SF2)/2 to obtain the visual clarity value QK ; Among them, kq3 and kq4 are the preset proportion coefficients, and kq4>kq3>0; and, the larger the value of the visual value QK, the more difficult it is for all managers to see the warning display content;
以及在可视化操作模块的显示面设定若干个温测点，实时采集温测点的温度值，将所有温度值进行求和计算并取均值得到显温值，显温值的数值越大，表明进行高亮度显示对可视化操作模块带来的损害和运行风险越大；并采集到显示区域的环境温度数据、环境亮度数据和粉尘浓度数据，通过归一化分析公式将显温值XW、环境温度数据QW、环境亮度数据QH和粉尘浓度数据QF进行归一化计算得到显表值XB；其中，vp1、vp2、vp3、vp4为预设比例系数，vp1、vp2、vp3、vp4的取值均大于零；显表值XB的数值越大，表明越需要适当提高显示亮度；And set several temperature measuring points on the display surface of the visual operation module, collect the temperature values of the temperature measuring points in real time, sum up all the temperature values and take the average value to obtain the displayed temperature value. The larger the value of the displayed temperature value, the greater the displayed temperature value. High-brightness display will bring greater damage and operational risks to the visual operation module; and collect the ambient temperature data, ambient brightness data and dust concentration data of the display area, and use the normalized analysis formula The display temperature value XW, ambient temperature data QW, ambient brightness data QH and dust concentration data QF are normalized and calculated to obtain the display value The values of vp3 and vp4 are both greater than zero; the larger the value of the display value XB, the greater the need to appropriately increase the display brightness;
将视况值QK和显表值XB与预设视况阈值和预设显表阈值分别进行数值比较，若视况值QK和显表值XB均超过对应预设阈值，则生成高亮度显示信号，若视况值QK和显表值XB均未超过对应预设阈值，则生成低亮度显示信号，其余情况则生成中亮度显示信号；事先设定高亮度显示信号、中亮度显示信号和低亮度显示信号分别对应一组亮度显示范围，可视化操作模块基于所生成的亮度显示信号确定相适配的亮度显示范围，若可视化操作模块的实际亮度处于相适配的亮度显示范围内，则不进行亮度调控；若可视化操作模块的实际亮度未处于相适配的亮度显示范围内，则自动将显示亮度调节至相适配的亮度显示范围内。Compare the visual status value QK and the display value XB with the preset visual status threshold and the preset display threshold respectively. If the visual status value QK and the display value XB both exceed the corresponding preset threshold, a high-brightness display signal is generated. , if the visual value QK and the display value The display signals respectively correspond to a set of brightness display ranges. The visual operation module determines the matching brightness display range based on the generated brightness display signal. If the actual brightness of the visual operation module is within the matching brightness display range, no brightness will be displayed. Control; if the actual brightness of the visual operation module is not within the matching brightness display range, the display brightness will be automatically adjusted to the matching brightness display range.
实施例三：本实施例与实施例1、实施例2的区别在于，若显示区域不存在管理人员，则生成预警推送分析信号并将其发送至数据治理平台，数据治理平台接收到预警推送分析信号时进行预警推送分析以确定最优管理人员，并将相应预警信息发送至最优管理人员的智能终端，能够在显示区域无人时自动选定最适管理人员并向其发送预警管理通知，有利于及时进行相应改善措施，进一步提升其智能化程度；其中，预警推送分析的具体分析过程如下：Embodiment 3: The difference between this embodiment and Embodiment 1 and 2 is that if there is no manager in the display area, an early warning push analysis signal is generated and sent to the data governance platform, and the data governance platform receives the early warning push analysis When there is a signal, early warning push analysis is performed to determine the optimal manager, and the corresponding early warning information is sent to the optimal manager's smart terminal. It can automatically select the most suitable manager when there is no one in the display area and send an early warning management notification to them. It is conducive to timely implementation of corresponding improvement measures to further enhance its degree of intelligence; among them, the specific analysis process of early warning push analysis is as follows:
获取到所有管理人员的智能终端信息，向所有管理人员发送预警指令并接收到管理人员的确认指令，将在规定时间内回复确认指令的管理人员标记为待选对象；采集到对应待选对象的管理时长，管理时长的数值越大，表明对应待选对象的管理经验越丰富；以及采集到待选对象处理对应预警操作的出发准备时长平均值以及延迟到达占比值，其中，延迟到达占比值是未按时到达并处理预警操作的次数占其总次数的百分比大小的数据量值，且获取到每次延迟到达的延迟时长，将所有延迟时长进行求和计算并取均值得到延时分析值；需要说明的是，出发准备时长平均值的数值越大、延迟到达占比值的数值越大且延时分析值的数值越大，则对应待选对象的处理越不及时；Obtain the smart terminal information of all managers, send early warning instructions to all managers and receive confirmation instructions from managers, and mark managers who reply to the confirmation instructions within the specified time as candidates for selection; collect the information of the corresponding candidates Management duration. The larger the value of the management duration, the richer the management experience of the corresponding candidate object; and the average departure preparation time and delayed arrival ratio of the corresponding early warning operation for the candidate object processing are collected, where the delayed arrival ratio is The data volume value is the percentage of the number of warning operations that did not arrive and be processed on time to the total number of times, and the delay duration of each delayed arrival is obtained, and all delay durations are summed and averaged to obtain the delay analysis value; required What is explained is that the greater the value of the average departure preparation time, the greater the value of the delayed arrival ratio and the greater the value of the delay analysis value, the less timely the processing of the corresponding candidate object will be;
通过公式将管理时长GS、出发准备时长平均值CS、延迟到达占比值YZ和延时分析值YF进行数值计算得到推析值TX；其中，ap1、ap2、ap3、ap4为预设比例系数，ap1、ap2、ap3、ap4的取值均大于零；并且，推析值TX的数值越大，表明对应待选对象的处理经验越丰富且越及时；将推析值TX与预设推析阈值进行数值比较，若推析值超过预设推析阈值，则将对应待选对象标记为可选对象；采集到可选对象与可视化操作模块之间的路径距离并标记为前行距离值，按照前行距离值的数值由大到小将所有可选对象进行排序，将位于最后一位的可选对象标记为最优管理人员。by formula The management time GS, the average departure preparation time CS, the delayed arrival proportion value YZ and the delay analysis value YF are numerically calculated to obtain the inferred value TX; among them, ap1, ap2, ap3, ap4 are the preset proportion coefficients, ap1, ap2 The values of , ap3 and ap4 are all greater than zero; and the larger the value of the inferred value TX is, the richer and more timely the processing experience of the corresponding candidate object is; compare the inferred value TX with the preset inference threshold , if the inference value exceeds the preset inference threshold, the corresponding object to be selected will be marked as an optional object; the path distance between the optional object and the visual operation module is collected and marked as a forward distance value. According to the forward distance All optional objects are sorted from large to small values, and the last optional object is marked as the optimal manager.
本发明的工作原理：使用时，通过建立企业数据治理框架、数据质量管理、数据安全管理、数据生命周期管理以及监控和优化，基于规范数据管理和操作流程，提高了数据的准确性和完整性，保护了数据的隐私和安全，实现了数据的优化和规范管理，能够应对目前对企业管理数据的管理所面临的诸多挑战，解决了目前企业数据管理中所存在的流程不规范、权限不明确、数据质量不高等问题，有助于满足现代企业的需求；且在进行监控和优化时基于数据治理中存在的问题和风险生成对应的预警信息，将对应预警信息发送至可视化操作模块进行信息显示预警，若显示区域存在管理人员，则通过预显检测分析以进行亮度自动调控，能够在发现问题和风险时进行预警信息的显示亮度自动合理调控，有助于显示区域所有管理人员看清预警显示内容；以及在显示区域不存在管理人员时通过预警推送分析以确定最优管理人员，并将相应预警信息发送至最优管理人员的智能终端，有利于及时进行相应改善措施，进一步提升其智能化程度。Working principle of the present invention: When used, by establishing an enterprise data governance framework, data quality management, data security management, data life cycle management, monitoring and optimization, and based on standardizing data management and operation processes, the accuracy and integrity of data are improved. , protects the privacy and security of data, realizes the optimization and standardized management of data, can cope with many challenges currently faced by the management of enterprise management data, and solves the current irregular processes and unclear permissions in enterprise data management. , low data quality and other issues, it helps to meet the needs of modern enterprises; and during monitoring and optimization, corresponding early warning information is generated based on the problems and risks existing in data governance, and the corresponding early warning information is sent to the visual operation module for information display. Early warning, if there are managers in the display area, the brightness will be automatically adjusted through pre-display detection and analysis. When problems and risks are discovered, the display brightness of the early warning information can be automatically and reasonably adjusted, helping all managers in the display area to see the early warning display clearly. content; and when there is no manager in the display area, early warning push analysis is used to determine the optimal manager, and the corresponding early warning information is sent to the smart terminal of the optimal manager, which is conducive to timely implementation of corresponding improvement measures and further enhances its intelligence. degree.
上述公式均是去量纲取其数值计算，公式是由采集大量数据进行软件模拟得到最近真实情况的一个公式，公式中的预设参数由本领域的技术人员根据实际情况进行设置。以上公开的本发明优选实施例只是用于帮助阐述本发明。优选实施例并没有详尽叙述所有的细节，也不限制该发明仅为的具体实施方式。显然，根据本说明书的内容，可作很多的修改和变化。本说明书选取并具体描述这些实施例，是为了更好地解释本发明的原理和实际应用，从而使所属技术领域技术人员能很好地理解和利用本发明。本发明仅受权利要求书及其全部范围和等效物的限制。The above formulas are all numerical calculations without dimensions. The formula is a formula obtained by collecting a large amount of data and conducting software simulation to obtain the latest real situation. The preset parameters in the formula are set by those skilled in the field according to the actual situation. The preferred embodiments of the invention disclosed above are only intended to help illustrate the invention. The preferred embodiments do not describe all details, nor do they limit the invention to specific implementations. Obviously, many modifications and variations are possible in light of the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, so that those skilled in the art can better understand and utilize the present invention. The invention is limited only by the claims and their full scope and equivalents.
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