ZENfra Third Party Data Source Management Instructions

As a user, you may encounter the need for alterations, corrections, and various actions in uploaded Third-party Data (user-defined data). The "Manage Source" feature has been designed to empower users with the capability to execute these actions effortlessly on the uploaded data files. The user can perform below mentioned actions to the existing data files:

• Renaming Source or Dataset or Fields(s) in the Dataset
• Adding a New Dataset (or) New Field(s) in the Dataset 
• Deleting the Source (or) the Dataset (or) the Field(s) inside the Dataset
• Reversing or Restoring the Editings
• Data Cleansing
• Relationship Editing (Between User-defined Data and System Data)
• Managing Permissions (Adding or Removing Read and Write permissions)

To access the Manage Source feature, follow these steps:

• Navigate to the ZENfra Menu Bar. Click on the "Manage Source" option. You will be directed to the Manage Source page, providing details on third-party data files uploaded to ZENfra through the source list table.

The Source List Table includes the following fields:

• Source:

Displays the third-party data file name provided during import.

• Dataset:

Displays all datasets (sheets) available inside that Source (Data File).

• Created by:

Displays the username of the individual who uploaded the data file to ZENfra.

• Created Time:

Displays the time when the user completed the configuration process during data file upload.

• Updated Time:

Displays the time when the user completed the entire importing process, including the data cleansing process.

• Current Version:

Displays the current version of the dataset (sheet), which changes if the user makes any edits.

• Actions (Source) Drop Down:

Add New Dataset: Action to add a new dataset (sheet) to the source (data file).

Edit: Action to edit the name of the source (data file).

Delete: Action to delete the data source from ZENfra.

• Actions (Dataset) Drop Down:

Version History: By clicking this action, the user can reverse or restore the editing made to the data file.

Edit: By clicking this action, the user is directed to the Edit Dataset page to perform the editing process in that specific dataset (sheet).

Delete: By clicking this action, the user can remove that specific dataset from the source (data file). (Note: This action cannot be reversed once performed)

Data Cleansing: This action allows the user to perform a data cleansing process in that specific dataset (sheet).

Steps To Rename Source:

• Click on the three dots in the Source Name row.
• Choose "Edit" from the dropdown menu.

• A popup box will appear for renaming the source.

• Click on the current source name in the popup.
• Enter the new desired name.
• Click "Save" to confirm the changes.

• Now you can see the source name has been changed.
  

Steps To Rename Dataset:

• Find the dataset you want to rename.
• Click the three dots in that dataset's row.
• Choose "Edit" from the dropdown menu.

• You'll be taken to the "Edit Dataset" page.
• In the top-left corner, you'll see the current dataset name.

• Click on the existing name and type in the new name.
• Click "Save" to save the renaming action.

• Now you can see the dataset name has been changed.
  

Steps To Rename Fields in A Specific Dataset:

• Find the dataset in which you want to rename the fields.
• Click the three dots in that dataset's row.
• Choose "Edit" from the dropdown menu.

• You'll be taken to the "Edit Dataset" page.
• In the table, find the list of field names under the "Field Name" column.
• Click on the field names you wish to rename and enter the new names.

• Now the field names of that specific dataset will be changed. It can be visible in the Analytics Feature. Here, you can ensure it by changes in the Current Version.

Steps for Managing Relationships Between Third-Party Data (User Define Data) Files and Device Logs

Step 1: Accessing the Edit Option for Dataset

• Navigate to the dataset you wish to manage relationships for and click on the three dots.
• Locate and click on the "Edit" option from the drop-down list to access the dataset editing page.

Step 2: Reviewing Relationships in the Dataset Table

• On the edit dataset page, observe the table displaying field names and associated information.
• Identify the "Relationship" column against each field name.

Step 3: Utilizing the Relationship Column

• To assign or remove relationships between the dataset and device logs, use the "Relationship" column.
• Click on the value in the "Relationship" column corresponding to the desired field. This action will open a popup box for relationship management.

Step 4: Performing Relationship Assigning or Removing Action

Within the popup box, you will find a comprehensive list of device log fields for all categories, facilitating the assignment or removal of relationships between third-party data and device log data. Follow these steps for effective relationship management:

1. Assigning a Relationship:

• Identify the required device log field from the list.
• Select the specific Device Log Report Field Name to establish a connection between the third-party data and the corresponding device log data by clicking on it.
• Click "Save" to apply and confirm the new relationship.

2. Removing an Existing Relationship:

• Identify the Device Log Report Field where a relationship is currently established.
• Unselect the field that is currently enabled as a relationship field between the third-party data and device log data by clicking on it.
• Confirm the action to remove the existing relationship.
• Click "Save" to apply and confirm the removal of the relationship.

Step 5: Finalizing Relationship Management

• Now, you will navigate back to the edit dataset page.
  
• On the edit dataset page, click the "Save" button located at the right top corner to complete the relationship management action.
• Your changes are now saved, and the relationship between the dataset and device logs is successfully managed.

Steps for Managing the Unique Field(s) in a Dataset:

• Click on the three dots of the dataset for which you want to manage unique fields.
• Select the "Edit" option from the drop-down list to navigate to the edit dataset page.

• On the edit dataset page, locate the "Unique" column displaying toggle buttons against each field name.
  

• Use the toggle buttons to make specific fields unique or non-unique.
• Activate the toggle button for a field to make it unique; Deactivate it to remove the uniqueness constraint.
• After configuring unique field settings, click the "Save" button at the right top corner of the edit dataset page to complete the action.

Steps to delete field(s) in the Dataset

• Navigate to the specific dataset and locate the three dots icon associated with the dataset you wish to delete field(s).
• Click on the three dots and select the "Edit" option from the dropdown menu. This action will direct you to the edit dataset page.

• Once on the edit dataset page, review the table displaying your dataset's fields. Locate the "Action" column, which features a delete icon against each field name.
  

• Identify the field(s) you intend to delete and click on the delete icon.
• After clicking the delete icon, a confirmation dialog will prompt you to verify your intention. To proceed with the deletion, select the "Yes" option.
• Upon confirming the deletion, a notification will be displayed, confirming the successful removal of the specified field(s) from the dataset. By this, the field(s) deletion action is performed successfully.

Note: The action of Deleting fields is permanent and cannot be undone. Versioning is in place, but retrieval of deleted data is Impossible. So, think before proceeding, as reversal is not an option.

Steps to delete a dataset from the Source

• As you are on the manage source page, click on three dots against the dataset that you intend to delete.
• Click on the delete option from the drop-down list, to delete the specific dataset from the source.
• After clicking the delete option, a confirmation dialog will prompt you to verify your intention. To proceed with the deletion, select the "Yes" option.
• Upon confirming the deletion, a notification will be displayed, confirming the successful removal of the specified dataset from the source. By this, the dataset deletion action is performed successfully.

Steps to delete a Third-Party Source from ZENfra

• As you are on the manage source page, click on three dots against the source that you intend to delete.
• Click on the delete option from the drop-down list, to delete the specific source from ZENfra.
• After clicking the delete option, a confirmation dialog will prompt you to verify your intention. To proceed with the deletion, select the "Yes" option.
• Upon confirming the deletion, a notification will be displayed, confirming the successful removal of the specified Source from ZENfra. By this, the source deletion action is performed successfully.

• As you are on the manage source page, click on three dots against the dataset that you intend to perform Data Cleansing.
• Click on the Data Cleansing option from the drop-down list, to navigate to the Data Cleansing page.

• On the Right Side of the page, click on the QC button at the top right corner to open the side panel.

• Clicking this New Rule button from that side panel will navigate you to the data cleansing rule creation page.

The Landing Page of the Data Cleansing Rule creation will be as shown in the above picture.

• Provide a Name for the rule you are creating (mandatory).
• Enable the "Apply During the Data Import" button to ensure that the rules you create will be applied during data import to ZENfra.
• On the left side of the page, locate the "Field Name" section, which displays the list of fields in that specific dataset.
• Next to that field, identify the "Action Field" and select the field for which you want to execute the data cleansing process. Note that you can only perform data cleansing on one column per rule. If you need to perform the same process for another column, create a separate rule.

• Utilize the rule to perform the following data cleansing processes:

• Advanced: You can also implement logical conditions for data cleansing by utilizing the conditions option given below.
• After creating the rule, click the "Save" button to finalize the rule creation process.

• Upon clicking "Save," you will be redirected back to the data cleansing page, where you can find the rule you created displayed on the right-hand side.

• Clicking on the rule will apply it to the data, and the output will be presented with highlights as shown in the picture. You can create several rules as needed.

• Finally, click the "Apply" button to complete the Data Cleansing action.
• The User Define Data will be displayed according to the data cleansing action performed in the Analytics Page.

• You will receive a popup notification confirming the completion of the data cleansing process.
• Now, you can quit the page by clicking on the "Cancel" button.

• Confirm the action completion by checking the change in the current version field of the specific dataset.
• The version type for the data cleansing rule is in decimal values.
• If the version is X before the data cleansing process, it will change to X.1 after completion.
• Subsequent data cleansing actions will result in versions like X.2, X.3, and so on.
• This versioning uniqueness applies exclusively to the data cleansing process.

As a user, it is common to make modifications to user-defined data, and there may be instances where you want to reverse these changes. The Version History option serves as a valuable tool in facilitating users to restore data to a desired version. Follow the steps below to achieve this:

• Navigate to the "Manage Source" page.
• Locate the dataset you wish to restore and click on the three dots against that dataset.
• From the drop-down list, choose "Version History."

• This action will open a popup table displaying the history of edits made as different versions. Proceed with the following steps. In the "Actions" field of each version, you will find two icons:

If a specific version’s "Actions" column does not display any icon, it indicates that your data is currently in that version. This functionality allows users to restore any version from the listed versions based on their requirements.

By following these steps, users can easily utilize the version history option to efficiently restore data to the desired state.

Note: the data downloading option is not available for versions related to the data cleansing process. In such cases, if you require the data with applied data cleansing, you can export it from the analytics page.