Introduction
This help document provides a comprehensive guide to prepare your data for the exploration of insights within Petavue. It includes instructions on defining relationships between connected data sources, configuring tags for fields, and enabling/disabling of tables/columns for analysis. This is an essential step to ensure seamless data exploration and reporting.
Prerequisites
Admin Access to Petavue
Understanding of your organization’s data structure and how different sources are connected.
Feature Description
The Data Preparation feature allows administrators to define relationships between connected data sources, ensuring accurate and meaningful data integration. This essential step creates a structured and reliable data foundation, empowering business users to effortlessly generate reports and derive valuable insights.
Step-by-step Instruction
All details of the connected data sources can be found under the Data Dictionary tab within the Data Hub.
The landing page displays all available data sources, along with a brief description of each source and the count of enabled tables.
You can edit the source description by hovering over the source, where the edit icon will appear. Click on the icon to open a pop-up, where you can update the description, and click Save to apply the changes.
To configure the details inside a data source, click on the name of the data source.
This will open a page. This page is segmented into:
A list of all tables available in the selected data source.
A description of the table, along with high-level details of the selected table, such as the number of enabled columns and the ability to enable or disable the table for analysis.
A list of all columns available in the selected table.
You can filter tables based on their analysis status.
Note: Only columns and tables that are enabled for analysis will be used during report execution. Ensure the necessary data sources are activated to include them in your reports.
Regardless of whether a column is available for analysis or not, if the entire table is disabled for analysis, the table will not be considered for any analysis. To enable or disable a table, simply toggle the button on or off as shown.
If a column or table is already used in Definitions or Connected Fields you will not be able to disable it.
The columns section displays a table. It has all the details of the columns in the selected table.
You can filter the columns by the following criteria:
Whether a column is enabled or disabled for analysis.
The data type of the column, such as number, string, etc.
The format of the column, such as currency, date, etc.
Tags, such as Default, Drill-down or Object View.
Data fill percentage, which refers to how many rows in the column is populated in the entire table.
Note: Tags help define the role of a column in your analysis. Here are the available tags and their functions:
Default: Columns tagged as "Default" contain essential information and are automatically included in the analysis output.
Drill-down: Columns tagged as "Drill-down" enable users to drill down into the definitions where they are applied, offering deeper insights into the data.
Object View: Columns tagged as "Object View" provide the ability to click and reveal all related values from the associated object when included in the output table, offering a comprehensive view of the dataset.
You can expand the details of the column by clicking on the row.
You can view a sample of the data contained in the column by clicking on the View Sample Data button.
This will open a pop-up displaying sample data from that column.
You can edit a field by clicking the edit icon that appears when you hover over the row. This will open a pop-up.
The pop-up contains two tabs.
The first is the General tab, where you can assign a name to the column. By default, the column name and field name are the same. However, you can assign a different name to the column, which will be displayed in the results instead of the original column name.In this tab, you can also add or modify the description of the column. Additionally, you can assign tags to the column. The format of the column is for informational purpose. You cannot edit them.
Note: The primary key(such as Id column from Salesforce Accounts table) of a table cannot be assigned the Object View tag.
The second tab is Connected Fields, where you can define relationships between tables across different data sources.
Example: The Account ID column in the Salesforce Opportunities table can be connected to the ID column in the Salesforce Account table. You can define this relationship in the Connected Fields tab by specifying the Target Column and providing a Connection Name for the relationship. The connection name will appear as a prefix in the output table to help identify the relationship between the connected tables.
After defining the relationship, if you view the Connected Fields tab for the ID column in the Salesforce Accounts table, you can see how other Salesforce tables, such as Opportunities, Cases etc., connect to the ID column of Accounts Table.
You can also add additional connected fields as shown below.
Notes
Ensure you have a thorough understanding of your organization’s data structure and how different sources are connected.
Defining relationships between tables is an essential step that enables the system to analyze data effectively.
Familiarise yourself with the tags configured for fields.
Regularly review and update relationships between data sources to maintain accuracy and consistency in reporting.
Conclusion
Data Preparation is essential for setting up a strong data foundation, enabling seamless exploration and accurate reporting. By performing these steps, admins can ensure that business users can easily access and analyze data to draw meaningful insights.