Why is Data Governance So Hard ? The Disconnect Between Business and Data

Data fails to reflect key business strategies and business activities systematically and organically. Each business stays fragmented, creating data silos and business silos.

Business develop phase

Business department lead

Department business, clear demand, fast implementation

Stage results, obvious effect, high recognition

agile business, agile response

Shallow problem

Changing business processes, changing data, lack of unified business and data architecture

There are many problems in cross-department business coordination and data sharing, which are often solved temporarily or cannot be solved

Lack of understanding of other business departments and business systems, and the business relationship and data connection between each other are unclear

Data Governance phase

IT department lead

Full collection (source layer)

Unified Standard (Standard Layer)

Full Fusion (Fusion layer: Foundation/Theme Library)

Shallow problem

Time-consuming and labor-intensive governance data can not meet the requirements when it is really used across departments

Departmental data, departmental standards, and governance phases often fail to identify cross-departmental data quality issues

Cross-departmental data standards identify departmental data quality issues, but do not drive business changes

Enterprises Need a Connected Data Architecture with a Business Perspective



AnyFabric, An Intelligent Knowledge Network of Data Assets


Establish a 3D coordinate system with core business processes as the X-axis, core business objects as the Y-axis, and innovative business activities as the Z-axis, realizing the identification and fabric of core business objects and core business processes, thus to use this as a basis for business development or data governance, and continuously monitor business objects and metadata changes.



Customer 360 °

Applied to customer intelligence, it quickly provides a comprehensive customer portrait view by integrating various customer data sources such as browsing, clicking, transactions, advertising, log files, CRM, etc

Business 360°

Integrate global data to provide a comprehensive business portrait view to help businesses identify or create opportunities to rapidly grow existing businesses or move into second growth curves.

Data compliance and audit

The system displays complete information such as the source, type, destination, and identity of information, helping enterprises perform data security audits more quickly and accurately.

Provide domain knowledge network to empower cognitive intelligence

Building domain knowledge network based on business objects, enabling cognitive intelligent application innovation, such as business cognitive search, intelligent question and answer, intelligent recommendation;


Provide data analysis and services

Easily support data analysis in an automated, intelligent manner and enable actionable insights.


Global business intelligence

With great flexibility, information is aggregated through data cleansing, aggregation, aggregation, and transformation capabilities, and business decisions are presented through business dashboards, metrics, and reports.


Weaving Trilogy of AnyFabric

First:Business Cognitive Model

Consider five aspects if a cognitive model based on the business to achieve business and strategy alignment is going to be built:

1.Is the business model oriented to the real business scenario and supported by strategy or theory?

2.What are the core business objects in this model? Is the relationship between them able to support the strategy?

3.Where do the core business objects come from? What is the maturity of business processes, systems and data? Is it a mature process with a mature system, or are the business processes and systems just running?

4.Based on the former, data governance is performed to form an enhanced data catalog.

5.Build a knowledge network of data assets and continuously monitor these business objects and metadata, thus forming a business object-centric data architecture.

First:Business Cognitive Model

Consider five aspects if a cognitive model based on the business to achieve business and strategy alignment is going to be built:

1.Is the business model oriented to the real business scenario and supported by strategy or theory?

2.What are the core business objects in this model? Is the relationship between them able to support the strategy?

3.Where do the core business objects come from? What is the maturity of business processes, systems and data? Is it a mature process with a mature system, or are the business processes and systems just running?

4.Based on the former, data governance is performed to form an enhanced data catalog.

5.Build a knowledge network of data assets and continuously monitor these business objects and metadata, thus forming a business object-centric data architecture.

Second: Enhance Data Catalog and Data Asset Knowledge Network

Based on the core cognitive model, the core business objects, core business systems and relationships are used to build an enhanced data catalog, i.e. to create a description of business objects and relationships:

1.Ontology model of business: Business is described by business objects, business processes, business forms, business fields, business standards and statistical rules.

2.Knowledge network of data assets: The data related to governance are collected and docked to the business cognitive model.

3.Normal monitoring: Discovering active business objects through metadata for global search and recommendation.

Second: Enhance Data Catalog and Data Asset Knowledge Network

Based on the core cognitive model, the core business objects, core business systems and relationships are used to build an enhanced data catalog, i.e. to create a description of business objects and relationships:

1.Ontology model of business: Business is described by business objects, business processes, business forms, business fields, business standards and statistical rules.

2.Knowledge network of data assets: The data related to governance are collected and docked to the business cognitive model.

3.Normal monitoring: Discovering active business objects through metadata for global search and recommendation.

Third: New Business Activity Development and Real-time Data Governance

Once the knowledge network is in place, data governance of the business can be performed. It is mainly divided into three steps:

1.Business combing: Research on the business, through which the main processes of the business, business tables of the main process nodes, standard tables of the business and statistical tables are sorted out.

2.Data governance: Based on the sorted out business processes, business standards and related standards to governance, form the corresponding subject library.

3.New business development: Develop according to business processes, standards and specifications, and the newly developed system data can be aligned with existing standards.

Third: New Business Activity Development and Real-time Data Governance

Once the knowledge network is in place, data governance of the business can be performed. It is mainly divided into three steps:

1.Business combing: Research on the business, through which the main processes of the business, business tables of the main process nodes, standard tables of the business and statistical tables are sorted out.

2.Data governance: Based on the sorted out business processes, business standards and related standards to governance, form the corresponding subject library.

3.New business development: Develop according to business processes, standards and specifications, and the newly developed system data can be aligned with existing standards.

Business Model:Free Combination, Free Choice

1.Open source code and documentation: Available for free download in the open source community. Symbiotic with AnyDATA Framework 2, AnyFabric's business cognitive model and data asset knowledge network need to be built based on AnyDATA Framework.

2.Commercialized knowledge-driven middle platform solutions: Including a series of enterprise-level security, performance and management optimization, while providing relevant built-in models and scenario capabilities, and also providing commercial technical support and services.

3.Ecological co-creation: Continuous processing and sharing of domain knowledge network with industry partners. The domain knowledge network can be provided as a domain knowledge data product in the form of service to all customers who need it.

1.Open source code and documentation: Available for free download in the open source community. Symbiotic with AnyDATA Framework 2, AnyFabric's business cognitive model and data asset knowledge network need to be built based on AnyDATA Framework.

2.Commercialized knowledge-driven middle platform solutions: Including a series of enterprise-level security, performance and management optimization, while providing relevant built-in models and scenario capabilities, and also providing commercial technical support and services.

3.Ecological co-creation: Continuous processing and sharing of domain knowledge network with industry partners. The domain knowledge network can be provided as a domain knowledge data product in the form of service to all customers who need it.

AnyFabric

Domain Cognitive Intelligence Driven

Instant Data Governance

CONTACT US

Advisory Email

Singapore, APAC

william.zheng@aishutech.com

Germany, EMEA

wolfgang.Korda@aishutech.com

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