How does the Nuvemshop to BigQuery integration work on Kondado?

You connect your Nuvemshop (Tiendanube) account to Kondado using API credentials, select which pipelines you want to replicate, and set your preferred update frequency. Data is automatically sent to BigQuery in structured format, ready for SQL queries and advanced analytics.

What Nuvemshop data can I replicate to BigQuery?

There are 25 available pipelines including Orders, Customers, Products, Abandoned Carts, Coupons, and Shipments. You get access to 981 fields such as total values, billing addresses, creation dates, and delivery tracking information.

How frequently is data updated in BigQuery?

The frequency is configurable based on your needs, ranging from every 5 minutes to daily intervals. This allows sales leaders to have updated data for decision making without overwhelming infrastructure.

What format does the data arrive in BigQuery?

Data is replicated in structured tabular format with properly typed fields for SQL queries. Each pipeline becomes a separate data structure in your Google Cloud project, facilitating complex joins and aggregations.

Can I combine Nuvemshop data with other sources in BigQuery?

Yes, you can replicate data from other sources such as social media, ERPs, or advertising platforms to the same BigQuery project. This enables data analysts to create unified business views by cross-referencing sales with marketing campaigns and logistics.

Do I need coding skills to set up the replication?

No code is required. Kondado provides a visual interface to select the 25 available pipelines and configure the BigQuery connection in minutes.

Can I send Nuvemshop data to destinations other than BigQuery?

Yes, besides BigQuery , you can send data to Power BI , Looker Studio , Google Sheets , PostgreSQL , MySQL, Excel, Redshift, SQL Server, or Amazon S3.

Send data from Nuvemshop (Tiendanube) to BigQuery

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Send Nuvemshop (Tiendanube) Data to BigQuery

To send Nuvemshop (Tiendanube) data to BigQuery, connect your store to Kondado and configure automated replication without writing any code. The platform offers 25 available pipelines including Orders, Customers, and Products that replicate directly to your Google Cloud data warehouse. You set the update frequency according to your needs, whether every 5 minutes, 15 minutes, hourly, or daily.

Kondado replicates Nuvemshop (Tiendanube) data to BigQuery automatically on a configurable schedule, making 981 fields from 25 different pipelines available for analysis and business intelligence.

Marketing managers, data analysts, and sales leaders use this connection to combine sales information with other sources in a single analytics environment. Operations teams can track cart abandonment metrics, coupon performance, and inventory levels with near-real-time data, making decisions based on current information.

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The Abandoned Carts and Promotion Discount Settings pipelines allow marketing managers to deeply analyze incomplete purchase behavior and measure the effectiveness of recovery campaigns sent to potential customers. With detailed Products and Product Variations data available in BigQuery, your team can cross-reference up-to-date inventory information with complete sales history to optimize restocking processes and quickly identify which items generate the highest profitability for your online store. Data analysts and sales leaders create sophisticated custom dashboards that combine this valuable Nuvemshop information with data from other e-commerce platforms or digital advertising tools used by the business.

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Nuvemshop (Tiendanube) data available for BigQuery

available pipelines

981

extractable fields

Available integrations

Integration	Description
Custom Fields	Includes fields such as id, created_at, and description, allowing customization of information related to specific resources.
Abandoned Carts	Contains data such as id, billing_address, and completed_at, enabling tracking of unfinished checkouts.
Promotion Discount Settings	Includes information on discount, discount_coupon, and discount_gateway, detailing discount settings applied to abandoned carts.
Abandoned Cart Coupons	Presents data on coupons used, allowing analysis of promotions that encourage purchase completion.
Abandoned Cart Products	Provides information on products included in the cart, such as id and has_stock_available, essential for understanding abandonment.
Applied Promotions for Abandoned Carts	Includes details on promotions applied, allowing analysis of the impact of offers on unfinished carts.
Categories	Contains information about product categories, facilitating the organization and search for items in the store.
Distribution Centers	Presents data on distribution locations, allowing efficient management of inventory and logistics.
Distribution Center Inventory	Includes information on available stock, facilitating control and replenishment of products.
Customers	Contains data such as id, contact_email, and created_at, essential for customer relationship management.
Customers: Custom Fields	Includes fields such as id, created_at, and value, enabling customization of customer information based on specific needs.
Coupons	Contains information about coupons, including id, code, and discount value, facilitating the management of promotions and offers.
Shipping Methods	Presents data on shipping methods, such as id, name, and cost, allowing analysis of available delivery options.
Products	Includes details about products, such as id, name, and price, essential for inventory and sales management.
Products: Custom Fields	Provides fields such as id, created_at, and value, allowing customization of product information as needed.
Products: Variations	Includes information about product variations, such as id, type, and price, facilitating management of different product options.
Products: Variations: Custom Fields	Presents fields such as id, created_at, and value, allowing customization of specific information for product variations.
Sales	Contains data on sales, including id, total value, and date, essential for performance analysis and financial reporting.
Sales: Custom Fields	Includes fields such as id, created_at, and value, allowing customization of sales information as needed.
Sales: Promotion Discount Settings	Presents information on discount settings, such as id, discount type, and value, facilitating promotion management.
Sales: Coupons	View information about coupons used in sales, including fields such as id, discount, and created_at.
Sales: Shipments	Track details of sales shipments, with fields such as tracking_number, shipping_address, and created_at.
Sales: Shipping Events	Examine events related to shipping, including fields such as event_type, event_timestamp, and tracking_number.
Sales: Products	Explore information about sold products, with fields such as product_id, quantity, and price.
Sales: Applied Promotions	Analyze promotions applied in sales, including fields such as promotion_id, discount_value, and created_at.

Custom Fields

Includes fields such as id, created_at, and description, allowing customization of information related to specific resources.

Abandoned Carts

Contains data such as id, billing_address, and completed_at, enabling tracking of unfinished checkouts.

Promotion Discount Settings

Includes information on discount, discount_coupon, and discount_gateway, detailing discount settings applied to abandoned carts.

Abandoned Cart Coupons

Presents data on coupons used, allowing analysis of promotions that encourage purchase completion.

Abandoned Cart Products

Provides information on products included in the cart, such as id and has_stock_available, essential for understanding abandonment.

Applied Promotions for Abandoned Carts

Includes details on promotions applied, allowing analysis of the impact of offers on unfinished carts.

How to send Nuvemshop (Tiendanube) data to BigQuery

Sync data automatically — no code, no manual exports.

Connect Nuvemshop on Kondado

Access the data sources settings in Kondado, select Nuvemshop (Tiendanube), and enter your store API credentials to establish the initial connection.

Configure BigQuery

Set BigQuery as the data destination, specifying the Google Cloud project ID and dataset where the 25 pipelines will be stored.

Select data and schedule

Choose which pipelines such as Orders, Customers, or Products to replicate and configure the update frequency to keep your dashboards automatically current.

Try out all the features for free for 14 days