can you summarize the below: Monitor: Ensure data quality by monitoring and alerting to potential data quality problems.
Defining data quality rules and requirements with the ability to extract metadata from its sources
Matching, joining, and merging: Capabilities of matching and merging related data within datasets through the use of a combination of methods such as algorithms, metadata, and machine learning.
Develop and implement business rules in a graphical and easy way for non-techies: Create, publish and manage business rules that are used to check data quality.
Support data evaluation through the dimensions of data quality mentioned in the regulations and specifications of the National Data Management Office
Data profiling is possible by performing a comprehensive data scanning process to find patterns and missing values.
The possibility of deleting duplicate data and data that does not comply with the data profiling process.
Possibility to convert erroneous data with a value into “good” data by correcting typos, standardizing and adjusting numeric values to fall between minimum and maximum values.

The ability to refine and link data (curation data) within systems to document data origins and how to process them so that different data sets are classified based on factors such as whether they contain personal information or other sensitive data and apply data governance policies to individual data sets according to their classification

The possibility of preparing an inventory list of the facilities’ data assets and managing their metadata
Possibility to import and store metadata
Create, implement and monitor data management workflows
Define employee roles and link them to data management functions
Identify data owners and data specialists and link them to the data they are responsible for
Providing the possibility of identifying personal data
Providing the possibility of alerts in different cases such as misuse of restricted data.
Managing policies by creating and editing policies and procedures, linking policies with related data, developing approval workflows and audit trails for each policy and procedure, issuing and publishing final documents and enabling them to be accessed by the target group.
Management of business terms (Glossary Business) by creating a repository to store and manage business terms with their associated definitions and the relationships between these terms.
Providing the possibility of data ramifications (lineage data) to identify data sources and their complete movements, providing information about the flow of data through systems and all operations that took place on them, and providing the ability to track the information flow.
Linking technical metadata elements with business terminology.
The possibility of evaluating the impact of change on the data when the integration process between them.
Providing metadata connectors for interconnecting different data sources such as ETL, application integration, data integration, search and business intelligence, reporting tools, modeling tools and database management system catalogs.
Providing reports and tools for measuring performance indicators for descriptive data