I. Product Overview

Data asset management is an effective means to promote the enhancement of data value. Currently, data asset management is confronted with the difficulty in tracing historical data structures and the chaos of data relationships. The data standards are inconsistent and it is difficult to integrate multi-source data. A series of problems and challenges such as real-time data changes and the difficulty in dynamically unifying data.

Merrill Lynch's "Data Asset Map Platform" is a new type of data asset management platform for enterprise-level users. The platform takes enhancing the value of data assets as its fundamental goal, is oriented towards building an intelligent enterprise, and takes artificial intelligence and knowledge graph technologies as its core. It is targeted at enterprise business personnel and data analysts, providing enterprises with data asset management capabilities based on business relationships, effectively solving data asset management problems, and promoting the optimization of enterprise business processes and data sharing and integration. Promote the enhancement of the value of data assets.

Ii. Product Features

1. Relationship discovery

By adopting reverse engineering, the data storage structure, table relationships, and the relationship between data and business are automatically discovered from historical data, enabling intelligent business and data sorting work.

2. Data Fusion

Based on business relationships, it helps enterprises effectively integrate data from different sources and to different standards, achieving comprehensive data integration within the enterprise.

3. Dynamic Perception

Dynamically perceive data changes and their impact on business and data, always maintaining consistency between data and business as well as the dynamic unity of related data.

4. Self-service analysis

Provide self-service data analysis tools for the general public to help users quickly complete data analysis work without coding and lower the threshold of data analysis work.

Iii. Product Application

1. Data asset standard management

With the goal of establishing the conversion relationship between data and standards, it avoids the implementation difficulties of historical data and system transformation caused by the traditional data standard management of defining first and then rectifying, effectively achieving the unified integration of multi-source data.

2. Data asset generation and management

Clarify the generation and circulation of data, build an enterprise knowledge graph, grasp the overall picture of enterprise data assets, and provide tool support for the full life cycle management of enterprise data from generation to extinction.

3. Data asset application management

Sort out the relationship between business and data, accurately grasp the actual presentation of business execution on data, effectively promote business collaboration and the application of cross-professional data assets, and truly leverage the value of data assets.

4. Data asset maintenance and management

By means of dynamic data perception, real-time monitoring and capture of data changes are carried out, and relevant data are synchronously modified according to the data changes to ensure the dynamic uniformity of data assets and enhance the ability to maintain and manage data assets.

5. Data Asset Quality Management

Based on the version management method, the version management control of the data relationship graph, business relationship graph, and enterprise knowledge graph is realized, effectively recording the evolution and maintenance process of versions, providing the ability to trace and review data asset management, and improving the quality of data assets.