From Ploomes to BigQuery: managed, scheduled, no code.
Creating a pipeline that sends data from Ploomes to BigQuery data warehouses takes only a few minutes with Kondado. And the whole integration from Ploomes to BigQuery is managed and executed by our platform. With Kondado, you can focus on extracting value from Ploomes data and combining it with other data in your BigQuery data warehouse
Connecting your CRM data to your data warehouse should not require dedicated engineering resources or complex API development. With Kondado, you can replicate data from Ploomes to BigQuery without writing any code, using a direct integration that runs on a configurable schedule tailored to your business needs. The platform handles the data extraction and loading automatically, ensuring your BigQuery environment always contains the latest information from your sales operations, deals, and client interactions. Simply select the specific data pipelines you need from the 36 available options, set your preferred update frequency ranging from every 5 minutes to daily intervals, and begin analyzing your complex sales data within minutes to drive better business decisions.
Kondado replicates your Ploomes CRM data to BigQuery on a configurable schedule, making your deals, clients, and sales records available for advanced analytics without manual exports or engineering resources.
Once your data arrives in BigQuery, you can analyze the Deals pipeline to track conversion rates across different funnels and stages, or examine the Clients (companies and individuals) pipeline to segment your customer base by ratings and sources for targeted marketing campaigns. The Sales Products pipeline enables you to identify which items drive revenue and which product families perform best, while Interaction Records help you understand client engagement patterns. Combine these datasets with information from Google Sheets or PostgreSQL to create comprehensive reports that span your entire business operations.
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Replicated to BigQuery
Ploomes data available for BigQuery
Tables Kondado writes into your BigQuery, on a schedule you control.
36
available pipelines
275
extractable fields
BigQuery
Destination
Available integrations
Positions
Table contains information about positions, including id, name, and associated user profile.
Cities
Table presents data about cities, including id, name, and associated state.
Cities: states
Table provides information about states related to cities, including id and state name.
Cities: countries
Table contains data about countries associated with cities, including id and country name.
Clients (companies and individuals)
Table presents information about clients, including id, name, email, and status.
Clients: ratings
Table provides data about client ratings, including id and rating name.
Clients: sources
Table contains information about client sources, including id and source name.
Clients: relationships
Table presents data about relationships between clients, including id and relationship type.
Clients: segments
Table provides information about client segments, including id and segment name.
Clients: status
Table contains data about client status, including id and status description.
Client Types
Includes fields such as id and name, allowing categorization of clients into different types for better management.
Departments
Contains fields such as id and name, facilitating the organization and structuring of departments within the company.
Documents
Presents fields such as id and filename, allowing management of documents associated with clients and sales.
Currencies
Includes fields such as id and currency, essential for financial management and conversion of values in different currencies.
Deals
Has fields such as id, ordernumber, and amount, allowing tracking and analysis of completed sales.
Deal Stages
Includes fields such as id, name, and ordination, which help define the progression of deals through different stages.
Deal Funnels
Presents fields that allow visualization and management of different sales funnels and their stages.
Deal Loss Reasons
Includes fields such as id and name, helping to identify and analyze the reasons why deals were not closed.
Deal Status
Presents fields that indicate the current status of deals, allowing better tracking of progress.
Products
Contains fields such as id and name, essential for managing and categorizing the products offered.
Product Groups
Includes fields such as id, name, and description, allowing for the categorization of products into specific groups for better organization and analysis.
Product Families
Contains fields such as id, name, and group_id, facilitating the organization of products into related families for more efficient management.
Proposals
Presents fields such as id, filename, and approval status, allowing for the management and tracking of proposals sent to clients.
Proposal Products
Includes fields such as proposal_id, product_id, and quantity, detailing the products included in each proposal for accurate tracking.
Proposal Approval Status
Contains fields such as id and name, allowing for the categorization of different approval statuses for submitted proposals.
Interaction Records
Includes fields such as id, type, and date, recording interactions made with clients for relationship analysis.
Tasks
Presents fields such as id, name, and status, allowing for effective management of tasks assigned to users within the platform.
Task Recurrence Intervals
Contains fields such as id and frequency, defining the periodicity of tasks for better work organization.
Task Types
Includes fields such as id and name, categorizing tasks into different types for easier management.
Email Reminder Types
Presents fields such as id and description, allowing the configuration of different types of email reminders for users.
Users
Table contains information about users, including fields such as id, name, and email, as well as role id and profile id.
User Suspension Reasons
Table lists the reasons for user suspension, with fields such as id and name, along with comments on the suspension.
User Profiles
Table presents user profiles, including fields such as id, name, and avatar url, along with phone and user language.
Sales
Table contains data on sales, including fields such as id, order number, date, customer id, and total sale amount.
Sales Stages
Table lists sales stages, with fields such as id, name, icon, and ordination of stages within a funnel.
Sales Products
Table contains information on sold products, including fields such as order id, product id, and quantity, along with unit price and discount.
Answers about sending Ploomes data to BigQuery automatically
How does the Ploomes to BigQuery connection work?▼
Kondado connects directly to your Ploomes instance using your API credentials to extract data from your selected pipelines. The platform then loads this information into your BigQuery dataset on your chosen schedule, handling all data type mapping and schema management without requiring manual intervention.
What specific Ploomes data can I replicate to BigQuery?▼
You can replicate 36 different pipelines including Deals, Clients (companies and individuals), Sales Products, Deal Stages, and Interaction Records. Each pipeline contains specific fields such as deal amounts, client ratings, product quantities, and task statuses, giving you comprehensive access to your sales and CRM data for analysis.
How frequently does my Ploomes data update in BigQuery?▼
You can configure update schedules ranging from every 5 minutes to daily intervals depending on your business requirements. This near-real-time synchronization ensures your analytics reflect current sales activities without the delays associated with manual data exports or spreadsheet updates.
Can I combine Ploomes data with other business sources in BigQuery?▼
Yes, BigQuery serves as a central repository where you can join Ploomes sales data with information from other platforms. Connect additional data sources through Kondado to merge your CRM information with marketing, financial, or operational datasets for unified reporting.
What format does Ploomes data take when loaded into BigQuery?▼
Each Ploomes pipeline loads into BigQuery as structured records with properly mapped data types and preserved relationships. The format allows you to write SQL queries immediately to analyze deal funnels, calculate conversion rates, or build custom dashboards in Looker Studio or Power BI.
Do I need technical skills to set up the Ploomes BigQuery pipeline?▼
No coding is required to establish the connection or maintain the data flow. Kondado provides a no-code interface where you authenticate your Ploomes account, select your desired pipelines, and configure your BigQuery destination through simple form inputs rather than complex API programming.
Can I send Ploomes data to destinations other than BigQuery?▼
Absolutely, Kondado enables you to replicate Ploomes data to multiple destinations simultaneously. While BigQuery offers advanced analytics capabilities, you can also send data to Google Sheets for quick sharing, Power BI for business intelligence, or PostgreSQL for operational databases.
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