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      Editing Datasets

      This article will walk the reader through how to edit and tailor datasets:

      Once the data is uploaded into CQ, any user that has been granted “Owner” rights to the dataset is able to edit it. To edit a dataset, navigate to the “Dataset Management” page, here the user will see a full list of all the datasets they have access to. To edit the dataset, hover over the “Action” dropdown and select “Edit Dataset.” (Note: If the user does not have ownership permissions to a dataset the “Action” dropdown will be greyed out.) The following menu will appear:

      Within this menu, the user can edit the following information:

      • General: Change the name of the dataset and the primary date field (details in the next section) and assign Tags to the dataset. These tags will be displayed next to the dataset dropdown and serve as a way for the dataset owners to share information such as sensitively level with the other users. For example: “Confidential”.
      • Sharing: Here dataset owners can assign rights to the dataset. This includes which users have “owner” or “read” access to the dataset, if the dataset is discoverable by the Cross Dataset Search feature and what information it can display.
        • “Owners” can modify / delete the dataset.
        • “Readers” can only view the dataset.
          • Note: Dataset user rights should be reviewed periodically to ensure they are assigned appropriately. Setting the permissions to “everyone” will allow new users / invited users to view those items immediately upon accessing ClearQuery.
        • Discoverability – if selected the dataset can be searched via Cross Dataset Search, if not selected the dataset will be omitted from the search results.
          • Additionally, the user can configure which attributes are displayed on Cross Dataset Search:
            • Label
            • Description
            • Tags
      • Fields: Users can set a custom display name for each field, which will appear in most features throughout ClearQuery on charts and tables. Additionally, dataset owners can add a field description and change the field format.
      • Automated Insights: the user can toggle which fields are visible or hidden - all hidden fields will be moved to the end of the list. The user can also change the order of the visible fields by dragging and dropping rows into the desired order.
        • Note: all users WILL be able to override these settings if they choose to configure a personal view via the customization cog.
      • AskCQ: Owners can assign synonyms to each field within the dataset, allowing users to ask questions using more naturally worded questions. For example:
        • An AskCQ question without synonyms: “Show me the top 10 ordering_customer_name with original_ordered_amount greater than 25000.”
        • An AskCQ question with synonyms: “Show me the top senders of transactions with amounts greater than 25000.”
          • By adding the synonyms, users are not required to know the specific field names within the dataset.
      • Data Exploration: Users can set which fields will be shown in the column headers, details, and which are hidden.  Drag and drop the field tags from one list to another as desired. The user can also change the order of the fields in the columns and in the details section via drag/drop.
        • Note: All users WILL be able to override these settings if they choose to configure a personal view via the customization cog.
      • Recommendation Engine: This function recommends and delivers insights based on how the data changes and evolves. It assists in configuring the data newsletter (sent via email) and helps Automated Insights to surface the most valuable charts upfront.
        • By default, this field will auto populate with the Primary Date Field. To update the engine, select which field you would like to base your recommendations off.
        • Here you can also disable the Recommendation Engine and check the overall status.
      • Filters: Dataset owners can configure which filters are shown and how they are organized.
      • Recent Uploads: Shows all the files that have been uploaded to create this dataset.
      • References: Users can see all objects associated with this dataset.
      • Sync: Allows the user to enable data syncing to a connector and configure the “look back” time frame or how many days of data to sync. Note: This function will not appear for all datasets, only the ones that are configured for a sync. 

      Configuring the Primary Date Field:

      If the uploaded dataset has a date field or multiple date fields, ClearQuery allows the user to assign one as the primary. To do this, navigate to the Dataset Management icon, find the appropriate dataset, hover over the "Actions" dropdown, and select "Edit Dataset." The dataset editor will pop up, and the user can see the Primary Date field in the bottom left corner. Select the appropriate field and click the "Edit Dataset" button.

      • Note: If the dataset does not have a date field, trend analysis will not be provided by ClearQuery.

      If you have additional questions regarding this topic, please reach out to your Account Manager or contact ClearQuery Support (support@clearquery.io).