Module Relationships

Updated on 2022-08-02 GMT+08:00

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This section introduces the relationships between main modules of data governance. See Figure 1 for details.

Figure 1 Module relationships

Data standards provide the core reference for data development and design. They are the result of data development. Data standards help ensure the consistency of data languages. They are the references for defining data, and are an important part of master data management. Data standards serve as a foundation for designing and formulating data quality management policies and rules. Security level classifications and owners specified in data standards facilitate data security management and are also important inputs for the management of data assets.

Master Data is one of the main ways that we can use to improve the quality of our data. In the course of data development, master data can be recorded, updated, and maintained in a unified manner. Master data management ensures the existence and consistency of core data for data applications and operations.

Data quality management is an important way to guarantee data accuracy, consistency, integrity, timeliness, uniqueness, and validity for various data applications and operations. It is also an important prerequisite for enterprises that use data to create value.

DataArts Catalog requires that metadata be collected and registered. This management of data assets makes it possible to use data. Users are able to understand data through the data asset module as well.

DataArts DataService means that standards, specifications, and requirements all need to be managed or controlled in data service development. These controls streamline the physical channels for data applications and data consumption.

DataArts Security means that the IT system needs to keep data secure to meet the compliance requirements of various regulations relevant to data applications during data development.

To effectively carry out data governance, there has to be effective organizational management, specified owners, appraisal systems, process regulations, data governance strategies and platforms.

Figure 2 DataArts Studio modules

DataArts Studio provides the functional modules to meet the data management requirements for ingestion, modeling, design, quality control, and service generation.

Parent topic: Data Governance Framework

Previous topic: Data Governance Modules

Next topic: Data Governance Organizational Architecture

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