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      Powerful server-side solution for collect and connect customer data

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      Create secure customer’s data pipelines to any data warehouses

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      Stories on how to use customer data for company growth

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      Learn how to install, set up, and use Renta tools.

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  • Product
    • First-party trackingFirst-party tracking

      Powerful server-side solution for collect and connect customer data

    • Marketing ETLMarketing ETL

      Create secure customer’s data pipelines to any data warehouses

  • Resources
    • BlogBlog

      Stories on how to use customer data for company growth

    • DocumentationDocumentation

      Learn how to install, set up, and use Renta tools.

  • Pricing
  • Connectors
Log in
Contact sales
Sign up
Renta
Marketing ETL
KeyCRM to Databricks

ETL KeyCRM data to Databricks

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Free for 7 days. No credit card required.

Source
Destination
Renta ELT is a simple way to create data pipelines in minutes. Not months.
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KeyCRM is a powerful CRM platform designed for seamless customer relationship management.
Renta Marketing ELT lets you effortlessly transfer data from KeyCRM to Databricks, ensuring fast, secure, and automated updates in your analytics environment.
Unlock deeper marketing insights and empower your team with reliable, up-to-date data for smarter decision-making.

Set up your ELT pipeline in 3 simple steps

Select KeyCRM as your data source and securely authenticate your account to initiate the data extraction process.

Selecting KeyCRM as the data source in Renta.
1Connect your source

Select KeyCRM as your data source and securely authenticate your account to initiate the data extraction process.

Selecting KeyCRM as the data source in Renta.
2Identify the destination
3Configure and synchronize
The data structure of the KeyCRM API

Renta supports 7 methods of data export using the KeyCRM API.

Accounts

Represents organizations or companies stored in KeyCRM. Contains data such as company name, industry, contact information, and account status.

Contacts

Stores individual contact records associated with accounts. Includes details like name, email, phone number, role, and relationship to the account.

Leads

Captures potential customers or prospects. Contains information such as lead source, contact details, status, and qualification data.

Opportunities

Tracks potential sales deals or business opportunities. Includes data on deal value, stage, expected close date, and associated account or contact.

Activities

Logs interactions and tasks related to accounts, contacts, or opportunities. Covers meetings, calls, emails, and follow-up actions with timestamps and outcomes.

Deals

Represents finalized or ongoing sales agreements. Contains deal amount, products or services involved, closing date, and deal status.

Tasks

Manages actionable items assigned to users. Includes task description, due date, priority, status, and related CRM entities.

Use cases

Unlock actionable KeyCRM insights

  • Sync real-time lead data from KeyCRM to Databricks for advanced sales analytics
  • Combine CRM and web analytics to reveal high-value customer segments in Databricks
  • Automate churn prediction by merging KeyCRM activity logs with Databricks ML models
  • Visualize sales pipeline trends by integrating KeyCRM deal stages with Databricks dashboards
  • Enrich marketing attribution models by blending CRM touchpoints with Databricks data
  • Forecast revenue by analyzing historical KeyCRM deals in Databricks notebooks
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Use cases: KeyCRM and Databricks integration
TEMPLATES

Start quickly with these use case templates

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Google Sheets
Snowflake

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Facebook
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Frequently asked questions
Reliable data ingestion for your Modern Data Stack

Free for 7 days. No credit card required.

Automate extraction from 100+ connections. 99.9% Uptime SLA.

Product
  • Marketing ETL
  • First-party data streaming
Popular connectors
  • Salesforce → Bigquery
  • Google Ads → Bigquery
  • Facebook Ads → Bigquery
  • Facebook Ads → Snowflake
  • Google Sheets → Bigquery
  • Google Sheets → Snowflake
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  • How to load LinkedIn Ads data into Google BigQuery

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