Send data from api4com to BigQuery

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Send api4com Data to BigQuery Automatically

Connecting your api4com voice communication data to BigQuery requires no coding or complex configuration. Kondado provides a direct integration that automatically replicates your call records and recharge information to Google’s serverless data warehouse on a configurable schedule. Simply authenticate your api4com account, select the specific pipelines you need, and define whether you want updates every five minutes, hourly, or daily.

Kondado replicates api4com Voice Calls and Recharge History data to BigQuery on a configurable schedule, enabling analysts to query call metrics and credit usage using standard SQL without manual data extraction.

Once your data arrives in BigQuery, you can combine api4com voice statistics with other business data sources to build comprehensive communication analytics. Marketing agencies can analyze call duration and pricing alongside campaign performance, while finance teams can monitor recharge patterns and credit consumption trends. The automated replication ensures your Looker Studio dashboards and Power BI reports always reflect current voice communication activity without manual CSV uploads.

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Kondado offers two essential pipelines for api4com users: Voice Calls and Recharge History. The Voice Calls pipeline delivers detailed conversation data including origin and destination numbers, call duration, and associated costs directly into your BigQuery dataset. Meanwhile, the Recharge History pipeline tracks credit movements with usernames, transaction dates, and recharge values for complete financial visibility.

With this data in BigQuery, customer success teams can calculate average handle times and cost per interaction by joining call records with support ticket data. Finance departments can build automated reports tracking prepaid credit consumption across different departments or campaigns. You can also blend this voice communication data with CRM information to analyze which customer segments generate the highest call volumes and associated costs.

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api4com data available for BigQuery

available pipelines

extractable fields

Available integrations

Integration	Description
Voice Calls	Table provides details about calls, including fields such as 'from', 'to', 'duration', and 'call_price'.
Recharge History	Table contains information about recharges, highlighting fields such as 'username', 'credit_date', 'value', and 'obs'.

Voice Calls

Table provides details about calls, including fields such as 'from', 'to', 'duration', and 'call_price'.

Recharge History

Table contains information about recharges, highlighting fields such as 'username', 'credit_date', 'value', and 'obs'.

See all available data →

Try out all the features for free for 14 days

How to send api4com data to BigQuery

Sync data automatically — no code, no manual exports.

Connect api4com Account

Log into Kondado and add api4com as a new data source by entering your API credentials in the authentication panel. The platform validates your connection and retrieves available pipelines including Voice Calls and Recharge History.

Configure BigQuery Destination

Select BigQuery as your destination and specify the target dataset where Kondado should create tables for your voice communication data. Provide the necessary project and dataset details to establish the connection endpoint.

Select Pipelines and Schedule

Choose which api4com pipelines to replicate, such as Voice Calls for conversation metrics or Recharge History for financial tracking, then set your preferred update frequency. You can configure intervals ranging from five minutes to daily updates depending on your analytics requirements.

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Frequently Asked Questions (FAQ)

Answers about sending api4com data to BigQuery automatically

How do I connect api4com to BigQuery without writing code? ▼

Kondado provides a no-code interface where you authenticate your api4com credentials and select BigQuery as your destination. The platform handles the schema mapping and data transfer automatically, creating tables for Voice Calls and Recharge History in your specified dataset. You simply configure your preferences through the web interface without writing SQL or API scripts.

What specific fields are available in the api4com Voice Calls pipeline? ▼

The Voice Calls pipeline includes essential communication metrics such as origin and destination numbers, call duration, and call_price for cost analysis. You also receive timestamps and connection details that allow you to calculate average handling times and peak usage periods. This structured data enables precise billing reconciliation and operational efficiency tracking within BigQuery.

How frequently does Kondado update api4com data in BigQuery? ▼

You can configure update schedules to run every five minutes, fifteen minutes, hourly, or daily depending on your reporting needs. This flexibility allows near-real-time monitoring for high-volume call centers while reducing query costs for less critical analytics. The automated schedule ensures your dashboards reflect recent activity without manual intervention.

Can I merge api4com call records with Salesforce or HubSpot data in BigQuery? ▼

Yes, once your voice data resides in BigQuery, you can perform SQL joins with CRM tables containing customer information or support tickets. This combination enables analysis of call costs by customer segment, campaign attribution for voice interactions, and correlation between recharge history and customer lifetime value. BigQuery's processing power handles complex queries across multiple data sources efficiently.

What data structure does api4com use when stored in BigQuery? ▼

Kondado creates structured tables for each pipeline, with Voice Calls containing fields like duration and call_price as numeric values and Recharge History storing credit_date as timestamps. The schema preserves data types from api4com, allowing immediate use in Looker Studio or Power BI without transformation. Each replication run appends new records or updates existing ones based on your configuration.

Can I analyze historical recharge patterns using the Recharge History pipeline? ▼

The Recharge History pipeline captures username, credit_date, value, and observation fields for every credit transaction in your api4com account. You can query this data to identify seasonal spending patterns, track departmental budget consumption, or forecast future credit needs based on historical trends. This financial visibility supports better cash flow management for voice communication expenses.

Is it possible to send api4com data to Google Sheets or PostgreSQL instead? ▼

While this page focuses on BigQuery, Kondado also supports sending api4com data to Google Sheets, PostgreSQL, MySQL, and other destinations. You can configure multiple destinations simultaneously to feed operational spreadsheets while maintaining a BigQuery data warehouse for deep analytics. This flexibility ensures the right teams access voice data in their preferred tools.

How can I calculate cost per call and total credit consumption in BigQuery? ▼

Join the Voice Calls pipeline containing call_price with the Recharge History pipeline tracking value fields to create comprehensive financial dashboards. You can aggregate daily spending, calculate average costs per minute, and monitor credit burn rates using standard BigQuery SQL functions. These calculations help finance teams optimize voice communication budgets and identify unusual spending patterns.

Get started for free

Get started for free

Get started for free

Send data from api4com to BigQuery

Get started for free

Send api4com Data to BigQuery Automatically

api4com data available for BigQuery

Available integrations

How to send api4com data to BigQuery

Connect api4com Account

Configure BigQuery Destination

Select Pipelines and Schedule

Hundreds of data-driven companies trust Kondado

Why Kondado?

Focus on extracting value from your data and leave the rest to us

Wherever you need

From wherever you need

Predictable pricing

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Frequently Asked Questions (FAQ)