From Bling! to BigQuery: managed, scheduled, no code.
Kondado replicates Bling! data to BigQuery automatically on a configurable schedule, enabling data analysts and marketing managers to analyze sales, inventory, and financial information directly in Google’s data warehouse.
To send Bling! data to BigQuery, connect your ERP account to Kondado and configure the desired pipelines without writing any code. The platform lets you select exactly which sales, inventory, and financial information to replicate, setting a configurable schedule ranging from 5 minutes to daily updates. Data analysts and marketing managers can keep their reports automatically updated in Google’s data warehouse.
With Kondado, you eliminate manual exports and outdated spreadsheets, consolidating all your business information in one place for faster analysis and data-driven decisions.
Using the Sales Orders and Products: Stock pipelines, you can create detailed analyses of sales performance and product availability in BigQuery. Accounts Payable and Accounts Receivable data allows sales leaders to track cash flow and financial projections accurately. This structured information enables operations teams to identify logistical bottlenecks and growth opportunities without relying on fragmented reports within the ERP.
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Replicated to BigQuery
Bling! data available for BigQuery
Tables Kondado writes into your BigQuery, on a schedule you control.
30
available pipelines
1528
extractable fields
BigQuery
Destination
API Version: V3
Available integrations
Cash and Banks: Transactions
Transaction records include fields such as id, date, amount, and description, enabling detailed financial control.
Categories: Stores
Information about categorized stores includes id, name, and description, facilitating organization and analysis.
Categories: Products
Data about categorized products includes id, name, and description, allowing efficient portfolio management.
Categories: Revenues and Expenses
Information about revenues and expenses includes id, name, and type, aiding in financial analysis.
Accounts Payable
Accounts payable data includes id, contact_id, amount, and due date, allowing control of financial obligations.
Accounts Receivable
Accounts receivable information includes id, contact_id, amount, and due date, facilitating the management of receivables.
Accounting Accounts
Accounting account data includes id, name, and type, essential for financial organization.
Contacts
Contact information includes id, name, email, and phone, facilitating communication and relationship management.
Deposits
Deposit records include id, date, amount, and account, allowing control of financial inflows.
Payment Methods
Data about payment methods includes id, name, and description, essential for managing financial transactions.
Product Groups
Table contains information about product groups, including fields such as id, name, and description, enabling efficient categorization of items.
Custom Field Information
Table provides details about custom fields, including id, name, and type, allowing data customization according to user needs.
Logistics
Table encompasses logistics information, with fields such as id, description, and status, facilitating the management of logistics processes.
Reverse Logistics
Table contains data on reverse logistics, including id, reason, and status, allowing tracking of returns and exchanges.
NFCe
Table gathers information on Electronic Consumer Invoices, with fields such as id, date, and total value, essential for fiscal management.
NFSe
Table covers data on Electronic Service Invoices, including id, date, and value, fundamental for service accounting.
Incoming NFe
Table contains information on Incoming Invoices, with fields such as id, date, and supplier, essential for inventory control.
Outgoing NFe
Table gathers data on Outgoing Invoices, including id, date, and customer, fundamental for sales management.
Nature of Operations
Table presents information on nature of operations, with fields such as id, description, and type, essential for fiscal categorization.
Production Orders
Table contains data on production orders, including id, product, and quantity, fundamental for manufacturing control.
Purchase Orders
Contains information about purchase orders, including id, associated contact, and order status.
Sales Orders
Includes details about sales orders, such as id, sale date, total, and order status.
Products
List of available products, including id, name, and associated categories.
Products: Stock
Information about product stock, including id, available quantity, and storage location.
Products: Structures
Details about product structures, including id and associated components.
Products: Suppliers
List of suppliers for products, including product id and supplier id.
Products: Stores
Information about stores selling products, including product id and store id.
Products: Variations
Details about product variations, including id and attributes of the variations.
Module Statuses
Contains information about module statuses, including id and status description.
Sellers
List of sellers, including id, name, and contact details.
Answers about sending Bling! data to BigQuery automatically
How does the Bling! to BigQuery pipeline work?▼
Kondado connects to the Bling! API and transfers your selected data to BigQuery at intervals you define. The process becomes fully automated after initial setup, keeping your information current without manual intervention.
What Bling! data can I replicate to BigQuery?▼
There are 30 pipelines available, including Sales Orders, Products: Stock, Accounts Payable, Accounts Receivable, Incoming and Outgoing NFe, and Logistics data. Each pipeline contains specific fields such as id, date, amount, and status.
How often does Bling! data update in BigQuery?▼
You control the update frequency based on your needs, choosing intervals of 5 minutes, 15 minutes, hourly, or daily. This flexibility lets you balance the need for current data with cost optimization.
What format does Bling! data arrive in BigQuery?▼
Data arrives in structured format, ready for SQL queries and visualization creation. Each pipeline becomes an organized structure that facilitates complex analysis and joining with other sources.
Can I combine Bling! data with other sources in BigQuery?▼
Yes, you can join Bling! information with data from BigQuery originating from other tools like Google Sheets, PostgreSQL, or other sources available in Kondado.
Are there ready-made dashboards available for Bling! data?▼
Yes, we offer pre-built report templates for Looker Studio and Power BI that connect directly to your BigQuery data, enabling immediate visualizations without building dashboards from scratch.
Do I need technical skills to set up the pipeline?▼
No coding or advanced API knowledge is required. Kondado's interface guides you through connecting Bling! and configuring the destination intuitively.
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