In the internet industry, architecture diagrams are an important tool used to visually display the architecture of software, systems, applications, and the relationships between their components. Common types of architecture diagrams include business architecture diagrams, application architecture diagrams, system architecture diagrams, technical architecture diagrams, deployment architecture diagrams, data architecture diagrams, product architecture diagrams, functional architecture diagrams, and information architecture diagrams.

Data Source: This is the starting point for data entering the system and can be various internal systems (such as ERP, CRM) or external systems (such as third-party APIs, social media).

Data Storage: The storage system is responsible for data persistence, including databases (such as relational databases, NoSQL databases), data warehouses, data lakes, etc.

Data Processing: The processing module is responsible for cleaning, transforming, aggregating raw data for subsequent analysis and use.

Data Analysis: The analysis module provides various analysis tools and methods to extract valuable information from the data.

Data Service: Provides processed and analyzed data in the form of APIs or other services for use by other systems or users.

Data Declaration: The architecture work declaration is one of the key documents in the architecture development method, describing the scope, methods, resources, and plans of architecture development. It defines the basic framework and expected outcomes of the architecture project, with data declaration being a part of it.

Data Principles: A set of fundamental guidelines and directives used to guide enterprise architecture design and implementation, ensuring consistency, flexibility, and scalability of the architecture, keeping architecture decisions consistent across different projects and teams.

Data Model: Defines data elements, their attributes, and the relationships between data elements. Outputs include conceptual models, logical models, physical models, data catalogs, etc.

Data Flow: The main outputs of data flow include data circulation, business mapping, etc., describing the flow and transmission methods of data within and between systems.

Clarify Data Flow, describing the process of data collection, processing, distribution to consumption from the source

Organize Data Structure, showcasing key data domains, table structures, data models

Unify Data Standards, assisting in data classification, naming conventions, metadata governance

Support Platform Construction, providing a basis for building data middle platforms, data lakes, data warehouses

Support Compliance Governance, meeting needs for data security, compliance, master data management

Data architecture primarily addresses three issues:

First, what kind of data the system needs;

Second, how to store this data;

Third, how to design the data architecture.

Connect to Business Architecture, analyze data needs, identify data types, collect data

Data Model Design, conceptual model, logical model, physical model

Data Governance, data security compliance, data quality management

Data Sharing and Opening, supporting business decisions, business innovation