Introduction

The Application Component View provides a visual representation of the software applications within an enterprise's architecture and the data exchanges between them.

Each application is depicted as a box, which may include smaller sub-boxes representing the master data owned by the application and secondary data objects utilized within its operations.

The master data is intrinsic to the application, forming the core of its function, while secondary data is provided through external data exchanges, depicted as lines or connectors between the applications. These lines illustrate the flow of information, integration, and dependencies between different software systems.

This diagram allows users to understand the structure and interactions between applications at a granular level, making it easier to track data ownership, manage dependencies, and optimize processes.

Master, Secondary, and Ghost data objects

We distinguish three types of data objects: Master, Secondary, and Ghost.

Name Explanation example
Master Master objects are owned and managed by its Master application. Typical examples include: the “Customer” data object is owned by the “CRM”.
Secondary Secondary data objects, are objects that sent through a data exchange, and that are not a master data of the receiving application. A data warehouse typically receives a lot of data objects through various data exchanges. Note, that a data warehouse can also be master of certain data.
Ghost When a data object is exchanged between application A and B, and application A is not its master, then we consider it ghost data. This is a probably either an error, or a remnant.

Purposes

Purposes of the Application Component View:

  1. Visualizing Application Architecture: Provides a clear and organized view of how applications interact with one another and the data they manage, helping users understand the current landscape of their IT infrastructure.
  2. Identifying Data Ownership: Shows which applications are responsible for maintaining master data, which can be essential for governance, compliance, and decision-making.
  3. Tracking Data Flows: Illustrates the flow of data between applications, highlighting dependencies and integration points, which can aid in troubleshooting and optimizing performance.
  4. Optimizing Integration: Helps identify potential bottlenecks, redundant data exchanges, or inefficient integration pathways, allowing users to streamline interactions between applications.
  5. Planning for Scalability: By visualizing both applications and their interactions, the view helps in planning for future growth, ensuring that the system architecture can scale effectively.
  6. Facilitating Communication: Enables enterprise architects, developers, and stakeholders to have a shared understanding of the application landscape, fostering collaboration across teams.
  7. Assessing Impact of Change: Provides insights into how changes in one application or its data flows might impact other parts of the system, supporting better change management and risk mitigation.
  8. Documenting the Architecture: Acts as a live documentation tool for the current state of enterprise applications and their interactions, ensuring alignment with business objectives and technical strategies.