Differences Between Data Structures
  • 02 Aug 2022
  • 2 Minutes to read
  • Dark

Differences Between Data Structures

  • Dark


Before deciding which Data Structure(s) to introduce into a process or workflow, it is paramount to understand the supported functionalities for each option. 

The first step towards this involves considering the nature of the process data as explained in its respective subsection. 

From there, the Data Structure Selection Matrix infographic is a visual reference to what each Data Structure can or cannot perform. 

Different kinds of Data Structures are suited to various applications and business needs. Users may construct their own custom Data Structures; however, not every use case will require one. 

Nature of Process Data

One way to help narrow down which Data Structure to use is to determine whether the process data, not the Flow Data, is in motion or at rest.

Data MovementDescriptionExample
Data In MotionThis type of data exists only within the generating process. While not typical, it can be saved externally via saving the outcome.A phone conversation or an approval process
Data at RestThis type of data exists past the process. The saved data is contextual, and while it cannot change, its related variables might. In other words, it is inactive data. A 'Person' is data at rest with variables such as 'Name,' 'Age,' and 'Clothing Size.' The 'Person' always remains a 'Person,' but the things related to the change.

Data Structure Selection Matrix

The Data Structure Selection Matrix infographic provides a visual guide for each Data structure' capabilities and limitations. 

Checkmarks denote support of a specific feature or factor, while Xs specify the opposite. For cases in between, clarifying text stands instead.

The number of check-marks does not indicate that a Data Structure should be used over the others. Rather, this infographic intends to narrow down the options. To better determine which Data Structure to use, please read more information about the individual Data Structures.

Understanding the Data Structure Selection Matrix

The above matrix displays several factors to consider when deciding which Data Structure to construct and how they may impact their process:

Performance ImpactThe amount of strain that a structure introduces to the overall performance of the system.
Can Be Saved To A DatabaseAllows data storage in a Table in the database; creates custom-generated steps related to the Data Structure.
Configuration FolderAutomatically generates a Configuration Folder where CRUD, other User Actions, and Visibility Rules for the Data Structure reside.
Entity FrameworkAdds an Entity Header Data Table, Folder View Report, and User Actions. Also uses Caching and is managed in Memory.
Folder BehaviorAdds a custom dashboard on a Folder, stores documents in Folders, and puts Assignments in Folders.
Process TrackingUtilizes Process Folders to track the state of a process.


Importing/Exporting Data Structures

In addition to using data and custom Data Types within a local environment, users may export data from Data Structures and import them to another Data Structure or a different Decisions environment. When deciding to migrate from one Data Structure to another, exporting then importing the data is a necessity. 

For further information on Data Structures, visit the Decisions Forum.

Was this article helpful?

What's Next