Noreja Entity Configurator
The Entity Configurator is a Noreja Productivity Tool for targeted editing of existing entity configurations based on a JSON file. It helps to adapt configurations faster and more structured than would be possible directly in the entity graph. For this purpose, the Entity Configurator provides several specialized features that can handle various tasks related to the maintenance, analysis, and optimization of entities. These include, among others, duplicating activities, adjusting timestamps, standardizing properties, cleaning up existing structures, renaming activities, comparing two JSON states, layouting entities, and a dashboard for structured evaluation. The goal is to make changes in a bundled and traceable manner within an existing configuration. This reduces manual interventions and significantly simplifies work on complex entity structures. The Entity Configurator is thus a central tool for the efficient further development and quality assurance of entity configurations in Noreja.
Main Features:
- Duplicator
- Timestamps
- Properties
- clean up
- rename
- Comparison
- Layout
- Dashboard
Duplicator
The Duplicator is used to quickly and structuredly create new activities based on an existing entity configuration. The starting point is always an imported JSON file that already contains an existing configuration. Instead of making changes directly in the entity graph, the user can edit, duplicate, and adapt this configuration much more efficiently in the Duplicator. The result is a new JSON that can then be downloaded.
Step 1: Upload JSON
In the first step, the user uploads a JSON file containing an existing entity configuration. After the upload, this file is available as a working basis for all further actions in the Duplicator.
Step 2: Prepare content and configure duplication
In the second step, the user can optionally define the basis on which new activities are to be generated. Two options are available for this.
Option A: Cluster Function
With the Cluster function, the user can insert a list of activity names. These names can be formulated differently but describe activities that are similar in content, for example, “Milling”, “Metal Milling”, “Cutting”, or “Preparing”. After clicking on ","Cluster"," similar entries are intelligently grouped. The clustering threshold can be adjusted via a slider, so that the grouping is either stricter or less strict.
The recognized cluster groups are then displayed in the lower area. These groups can be expanded so that the user can see which individual values are contained in each group. In addition, it is already visible how the later WHERE clause in the SQL is likely to be composed.
Option B: Tuple Option
Alternatively, the user can use the tuple option. Here, the data is inserted in tabular form. The structure is based on tuples: on the left side is the specific process activity or the later name of the activity, on the right side are one or more values that are to be adopted into the WHERE clause later. Multiple values can be specified separated by semicolons.
These tuples are also intelligently grouped. If identical labels appear multiple times on the left side, they are automatically combined. The resulting tuples are displayed in the lower area. These can be clicked to understand which values flow into which activity.
Select source activity
Once the inputs have been prepared using the cluster or tuple option, the user selects an existing activity to be duplicated as a template. This selection is made via a dropdown with the already existing activities.
After selection, the existing settings of this source activity are displayed. These include, among others, the title, the WHERE clause, the JOIN clause, and existing relationships from the entity graph.
Use variables
In the title, the user can use the variable %VAR%. This marks the position where the name of the respective cluster group or tuple will be automatically inserted later. In this way, a separate activity with a suitable name is created for each prepared group or tuple.
In the WHERE clause, the variable %LIST% can be used. At this point, the grouped values are inserted, so that each generated activity contains exactly the corresponding entries in its WHERE clause.
Optionally, the JOIN clause and the relationships can also be adjusted. Here too, it is possible to work with variables if this is useful for the desired configuration.
Apply
With Apply, the new activities are generated based on the selected template and the prepared groups or tuples. The configured variables are automatically replaced with the respective values, so that the new activities are directly named appropriately and filled with content.
Step 3: Adjust layout
In the third step, the user can easily adjust the layout of the generated activities. The goal is to display the new elements clearly and neatly on the screen later.
Step 4: Merge and download JSON
When the configuration is complete, the user can click on Merge and Modify. This will generate a new JSON with the changes made. This new JSON can then be downloaded from the bottom right of the screen.
Timestamp
The Timestamp feature is used to specifically find and collectively replace date or timestamp values within an existing entity configuration. The basis here is also an imported JSON file with an already existing configuration. The search is carried out exclusively within the WHERE clauses of the entities. This way, existing time references can be quickly updated without having to manually adjust each configuration in the entity graph. The result is an updated JSON that can then be downloaded.
Step 1: Upload JSON
In the first step, the user uploads a JSON file containing an existing entity configuration. After the upload, this file is available as the basis for further processing in the Timestamp feature.
Step 2: Enter Timestamp Pattern
In the second step, the user enters a timestamp pattern to search for within the existing entities. The search is carried out exclusively in the WHERE clauses of the entity configurations.
For example, if the value 2026-01-01 is entered, the system checks where exactly this pattern occurs in the existing WHERE clauses. The goal is to quickly identify existing date values and prepare them for later adjustment.
The value entered in this step also serves as the new target value for later replacement. For example, an existing date like 2025-01-01 by 2026-01-01 can be replaced if a date range needs to be updated.
Step 3: Review hits and edit if necessary
In the third step, all found hits are displayed. The user sees where the searched pattern was found within the WHERE-Clauses and what the respective replacement would look like.
This allows checking which areas of the JSON are affected and which adjustments are made before the actual change. Additionally, there is the option to manually edit individual hits. Using the function Edit on the right side, the respective WHERE-Clause can be explicitly adjusted again.
This allows the user to control, refine, and ensure that all proposed changes are substantively correct.
Step 4: Change timestamp and download JSON
Once all hits have been reviewed and the desired adjustments made, the user can apply the change in the fourth step. To do this, the function Change timestamp is executed.
Subsequently, all affected timestamps in the JSON are adjusted accordingly. Additionally, it is displayed how many timestamps were changed and how many replacements were performed in total.
Finally, the updated JSON can be downloaded from the bottom right of the screen.
Properties
The Properties feature serves to standardize and specifically extend existing properties of entities or activities within an entity configuration. The basis here is also an imported JSON file with an existing configuration. The goal of the feature is to bring all activities based on the same table to a common standard, so that ultimately consistent properties are available across all relevant entities. Additionally, new properties can also be manually added and incorporated into the configuration. The result is an updated JSON that can then be downloaded.
Step 1: Upload JSON
In the first step, the user uploads a JSON file containing an existing entity configuration. After the upload, this file is available as the basis for further processing in the Properties feature.
Step 2: Select Table
In the second step, the user selects a table. All activities or entities that were created from the same table are displayed grouped together.
For example, if multiple activities are based on an SAP table like AFKO, they are considered together within the selection. The user then selects the desired table from the dropdown for which the properties are to be standardized or extended.
Step 3: Select Entities and Prepare Properties
After selecting a table, in the third step, all associated entities or activities are displayed in a multi-select list. The user can specifically select which activities should have their existing properties supplemented or aligned.
On the right, it is also shown how many of the already existing properties are available for the selected entities. The system always bases this on the maximum number of properties present within the respective activities. For example, if an activity already has 10 properties, this is considered the maximum possible state that the standardization is based on.
Align properties
The goal of this step is to standardize properties across multiple activities. The user can use the multi-select option to determine for which entities the properties should be supplemented. After selection, these can then be added via the corresponding function, so that the affected activities receive the same property status.
Add new properties
Additionally, it is possible to manually define completely new properties. Free text fields are available for this purpose. Among other things, the following can be entered:
Name
Neo4j Data Type
Data Type in the source system
Table name
Table Schema
These new properties can also be added to the existing configuration.
Step 4: Enrich properties and download JSON
Once the desired entities have been selected and the existing or new properties prepared, the user can click on Enrich.
This will incorporate the properties into the JSON and supplement the selected entities accordingly. Finally, the updated JSON can be downloaded from the bottom right of the screen.
Cleanse
The Cleanse feature is used to specifically remove existing elements from an entity configuration. The basis here is also an imported JSON file with an existing configuration. The user can choose whether to cleanse activities, relationships, or tables. Depending on the selected category, the corresponding elements are deleted from the JSON. The system also takes existing dependencies into account to ensure that no invalid links remain. The result is a cleansed JSON that can then be downloaded.
Step 1: Upload JSON
In the first step, the user uploads a JSON file containing an existing entity configuration. After the upload, this file is available as the basis for further processing in the Cleanse feature.
Step 2: Select category
In the second step, the user selects which category should be cleaned up. Three options are available for this:
Activities
Relationships
Tables
The selection in this step determines which elements can be displayed and selected for deletion in the next step.
Step 3: Select Elements
Depending on the selected category, the corresponding elements from the JSON will be displayed in the third step.
If Activities is selected, all existing activities from the JSON will be displayed.
If Relationships is selected, all existing relationships will be displayed.
If Tables is selected, all tables used in the JSON will be displayed.
The user can then, via a multi-select option select multiple elements or all displayed elements that are to be cleaned.
Behavior for Activities
When activities are deleted, the system also removes all existing relationships connected to these activities. This ensures that no open or invalid relationships remain in the JSON.
Behavior for Relationships
When relationships are deleted, only the selected relationships are removed. The associated activities remain. This may result in activities still being present in the graph even if their connections have been removed.
Behavior for Tables
When tables are deleted, the system removes all activities associated with these tables. Additionally, all relationships belonging to these activities are also deleted.
Step 4: Clean and Download JSON
Once the desired selection has been made, the user can, in the fourth step, click on Clean and Modify.
This will remove the selected elements from the JSON. The cleaned JSON can then be downloaded from the bottom right of the screen.
Rename
The Rename feature is used to rename existing activities within an entity configuration in a targeted and rule-based manner. The basis here is also an imported JSON file with an existing configuration. The user can select several activities and then define which text components in their names should be searched for and replaced by other values. In this way, designations can be quickly and consistently adjusted without having to edit each activity individually. The result is an updated JSON that can then be downloaded.
Step 1: Upload JSON
In the first step, the user uploads a JSON file containing an existing entity configuration. After the upload, this file is available as a basis for further processing in the Rename feature.
Step 2: Select Activities
In the second step, all existing activities from the JSON are displayed. The user can select one or more activities here via a ","multi-select selection",". Alternatively, it is also possible to directly select ","all activities",".
This determines which activities the later defined renaming rules should be applied to.
Step 3: Define Replacement Rules
In the third step, the user can create various replacement rules. Two input fields are available for this purpose.
Left Field
In the left field, enter the text string to be searched for. This can be a single word or several connected words.
Right Field
In the right field, enter the text string that should replace the searched content.
The user can add any number of these rules. This makes it possible to define multiple search and replace patterns in parallel, which are then applied to the selected activities.
Step 4: Check preview
In the fourth step, a preview of the replacements is displayed. There, the user can see exactly what the renaming will look like after applying the defined rules.
The changed content is highlighted in a turquoise display, making it immediately clear which parts have been adjusted after renaming. This allows the user to check the planned changes in advance and verify whether the desired result is achieved.
Step 5: Rename and download JSON
If the preview matches the desired changes, the user can click on Rename and change .
This applies the defined replacements to the JSON and renames the selected activities accordingly. The updated JSON can then be downloaded from the bottom right of the screen.
Comparison
The Comparison feature is used to compare two different entity configurations with each other and to make changes transparently visible. The basis is an imported JSON file that is matched with a second JSON file. The goal is to quickly identify which activities, relationships, tables, or properties have been added, removed, or changed between two versions. The feature is exclusively for analysis and informative comparison. No merge of the two JSON files takes place. Therefore, no new merged JSON is created here for further processing.
Step 1: Upload first JSON
In the first step, the user uploads the JSON that is to be considered the current or to-be-checked version. This JSON forms the basis for the subsequent comparison.
Step 2: Upload second JSON and start comparison
In the second step, the user uploads another JSON. This could be, for example, an older version of the same entity configuration.
Once both JSON files are available, the user can start the comparison. A comparison between both configurations is then performed to evaluate differences in a structured manner.
Step 3: Analyze differences
After the comparison, the user receives an overview of the detected changes between the two JSON files.
Compare activities
It shows how many activities have been newly added, how many have been removed, and how many have been changed. Additionally, the newly added activities are displayed separately on the right side.
Compare Relationships
On the left side, the user sees which changes have been identified in the relationships. This quickly reveals which connections have been newly added, removed, or changed.
Compare Tables and Properties
In addition, the comparison also shows which tables have been newly added and which changes exist in the properties. This makes it possible to understand not only the structure of the activities but also their technical design.
Compare WHERE-Clauses
The comparison of WHERE-clauses within the activities is also particularly relevant. Changes are displayed directly and visibly. The previous value appears red and struck through, while the new value turquoise is highlighted. This allows the user to quickly identify where filter logics or date ranges have changed.
Step 4: Classify the result
The Comparison feature is solely for information and analysis. No merge between the two JSON files is performed, and no changes are automatically adopted.
In this case, downloading a new JSON is not functionally relevant, as no merged state is generated. The feature thus specifically helps to make differences between two configuration states visible and to evaluate them professionally.
Layout
The Layout feature is designed to specifically optimize the spatial arrangement of activities or entities within an entity configuration. The basis here, too, is an imported JSON file with an existing configuration. The goal of the feature is to make the subsequent visualization of the entity graph clearer, more meaningful, and more efficient. Especially with a large number of entities, a structured layout helps to maintain an overview more quickly, find new elements more easily, and make changes more targeted. The result is an updated JSON in which the layout information is stored and which can then be downloaded.
Step 1: Upload JSON
In the first step, the user uploads a JSON file containing an existing entity configuration. After the upload, this file is available as a basis for further processing in the Layout feature.
Step 2: Select Layouting Algorithm
In the second step, the user selects the desired layouting algorithm. This determines the logic by which the activities or entities will later be arranged on the screen.
Two different algorithms are available.
Star / Hub-Satellite
In this algorithm, central nodes or entities are arranged as hubs. Entities connected to these central elements are positioned as satellites around these hubs. This creates a structured representation with clear centers and associated surrounding elements.
Name Similarity
This algorithm examines the names of activities or entities. Elements with similar text components or similar names are grouped and arranged spatially close to each other. This makes it easier to identify activities that are related professionally or linguistically.
Step 3: Configure Layout Settings
In the third step, the user can make additional settings for the layout. This allows the subsequent arrangement to be further adapted to one's own requirements.
Possible settings include:
Hub Distance
Determines how close or how far apart the different hubs are arranged from each other.
Satellite Radius
Determines the distance at which satellites are positioned around a hub.
Maximum Hubs per Row
Defines the maximum number of hubs that can be arranged in a row.
Start X and Start Y
Here, the starting coordinates for the arrangement can be set.
In the lower section, similar hubs are also displayed, giving the user a first impression of how the grouping is interpreted in the selected layouting.
Step 4: Apply Layout and Download JSON
Once the desired algorithm has been selected and the settings configured, the user can click on Layouting in the fourth step.
This writes the layout information into the JSON. The updated JSON can then be downloaded from the bottom right of the screen.
Dashboard
The Dashboard feature serves to structurally evaluate an existing entity configuration and present it as a compact overview. The basis here is also an imported JSON file with an already existing configuration. The goal of the feature is to quickly gain a detailed overview of the structure, scope, and central contents of the JSON. The Dashboard thus particularly supports the analysis, quality assurance, and technical classification of an existing configuration. Unlike other features, the focus here is not on editing, but on transparent evaluation.
Step 1: Upload JSON
In the first step, the user uploads a JSON file containing an existing entity configuration. After the upload, the JSON structure is analyzed and clearly presented in the dashboard.
Step 2: Display JSON Structure Overview
In the second step, the user receives a summary overview of the most important key figures of the loaded configuration.
Among other things, the following are displayed:
Number of activities
Number of relationships
Number of different properties
Number of date fields used
Number of tables
Number of referenced activities
File size of the JSON file in kilobytes
These key figures help to quickly assess the scope and complexity of the configuration.
Step 3: Check details by tables and content
Further details on the JSON structure are displayed in the lower part of the dashboard.
WHERE clauses by table name
The existing WHERE clauses are displayed grouped by table name. This allows the user to understand which filter logics are based on which tables. A copy function is also available for the WHERE clauses.
Statistics on used tables
Additionally, statistics on the used tables are displayed. This information can also be copied via a copy button.
Created Timestamps and Change Timestamps
Below, all used Created Timestamps, as well as all Change Timestamps are displayed in list form. This makes it transparent which time fields are used within the configuration.
Properties and Relationships
In addition, the dashboard shows a complete list of the properties used and the existing relationships. This allows the user to understand the technical components of the configuration in detail.
Step 4: Use results for analysis and documentation
The Feature Dashboard primarily serves the structured evaluation of an existing entity configuration. It provides a quick overview of key figures, tables, WHERE clauses, timestamps, properties, and relationships, thereby supporting both the analysis and documentation of the JSON content.