Schema mapping

Renta provides flexible tools to define what data and in what format will be loaded into your warehouse. You can trust our expertise by choosing ready-made templates, or take full control of the process by configuring each field yourself.

Schema configuration modes

When creating an integration, two main approaches to defining the data schema are available:

Pre-built templates

This is the recommended way for a quick start. Templates are proven configurations designed by Renta analysts.

1. Automation. Renta will automatically create the necessary pipelines, tables in the Data Warehouse, and configure the relationships between them.

2. Best practices. The schema already contains all the necessary fields for building standard reporting (for example, combining ad statistics with campaign metadata).

3. Time saving. You don't need to study the source API documentation to understand which fields are needed for a report.

Custom schema

Suitable for advanced users who need full control.

1. Table selection. You decide which API endpoints or database tables need to be extracted.

2. Field filtering. Ability to exclude unnecessary columns (PII data, technical fields) to optimize storage costs.

Using Pre-built templates

Templates are selected during the data source configuration stage. Let's consider the process using an integration example where a template automatically deploys a complex data structure.

Creating a pipeline from a template

Using a ready-made template to automatically create a data schema.

Select Pre-built templatesStep 1

In the pipeline creation wizard, at the integration configuration stage, select the Pre-built templates option in the Integration type field.

Choose a templateStep 2

From the list of templates that appears, select the one suitable for your task (e.g., LinkedIn Ads Performance Report). Renta will show the template description and the list of tables that will be created.

Complete creationStep 3

Click Create pipeline. The system will automatically create and configure all necessary data flows.

Schema mapping

Regardless of whether you chose a template or created the integration manually, you can always change the list of extracted fields. This allows you to adapt data to changing business requirements.

Changing field selection

Adding and removing fields in an existing pipeline.

Navigate to settingsStep 1

Open the Pipelines section, find the desired pipeline, and click the edit icon (pencil).

Configure MappingStep 2

In the Parameters block, you will see a list of all fields available in the source API.

1. Checked. The field will be loaded into the destination table.

2. Unchecked. The field will be ignored.

Save changesStep 3

Click Update pipeline. On the next run, Renta will automatically update the table structure in your Data Warehouse (add new columns if they appeared).

Handling schema drift

Renta automatically handles changes in data structure:

1. Adding fields. If you added a new field in the mapping settings, Renta will automatically add the corresponding column to the destination table during the next load (ADD COLUMN).

2. Data types. Renta automatically converts source data types to the destination warehouse data types (BigQuery, Snowflake, etc.), ensuring compatibility.