1. Data Preparation
2. Data Imports
3. Import Pipedrive

Here is a quick 3-step process for querying Pipedrive data in Holistics. Pipedrive reporting in Holistics requires you to connect your Pipedrive database.

Step 1: Set up a new data source to allow data import

Set up your database to allow write access for a given data source. Setting up separate schema that allows write access is recommended. Please have a look at our docs on how to connect your database to Holistics.

Step 2: Create a new data import

Click Add new data import in Manage -> Data Imports

Next:

1. Choose Pipedrive as import source.
2. Choose the data source from which you want import.
3. Select a table in your database to preview it.

Step 3: Select/Create Destination Table

Select your destination data source and schema name. Then enter your destination table name.

Step 4. Validate input and destination table structure

Specify the destination data source, schema name and table name that you would like to import the data into. Choose your sync configuration, and click on the Validate Sync Config button to validate the table setup. The column definitions are also automatically generated from the source data. The data type of each column can be modified as you see fit.

Schedules for the current data import can be modified by selecting +Add Schedule. Optionally, data imports can be executed manually by clicking on the Execute link from the list of available data imports, after you have saved the import job.

Step 5. View data import status from job list

Once a data import has been executed, either manually or based on its schedule, a new job corresponding to the import job will be created to track its progress.

Users can click on the Job History tab to refresh and keep track of jobs that have run. Users can also click on the Logs link to view the detailed logs of each job execution.

Additional data

Here are details for our supported API endpoints.

Activities

COLUMN	TYPE
id	int
company_id	int
user_id	int
done	boolean
type	varchar
reference_type	varchar
reference_id	int
due_date	date
due_time	varchar
duration	varchar
add_time	timestamp
marked_as_done_time	timestamp
subject	varchar
deal_id	int
org_id	int
person_id	int
active_flag	boolean
update_time	timestamp
gcal_event_id	varchar
google_calendar_id	varchar
google_calendar_etag	varchar
note	varchar
participants	json
person_name	varchar
org_name	varchar
deal_title	varchar
assigned_to_user_id	int
created_by_user_id	int
owner_name	varchar
person_dropbox_bcc	varchar
deal_dropbox_bcc	varchar

Deals

COLUMN	TYPE
id	int
creator_user_id	int
user_id	int
person_id	int
org_id	int
stage_id	int
title	varchar
value	double
currency	varchar
add_time	date
update_time	date
stage_change_time	date
active	boolean
deleted	boolean
status	varchar
next_activity_id	int
last_activity_id	int
lost_reason	varchar
visible_to	int
close_time	date
pipeline_id	int
won_time	date
first_won_time	date
lost_time	date
products_count	int
files_count	int
notes_count	int
followers_count	int
email_messages_count	int
activities_count	int
done_activities_count	int
undone_activities_count	int
reference_activities_count	int
participants_count	int
expected_close_date	date
last_incoming_mail_time	date
last_outgoing_mail_time	date
stage_order_nr	int
rotten_time	date
weighted_value	double
cc_email	varchar
org_hidden	boolean
person_hidden	boolean
average_time_to_won	numeric string
average_stage_progress	double
age	numeric string
stay_in_pipeline_stages	jsonb

Organizations

COLUMN	TYPE
id	int
company_id	int
owner_id	int
name	varchar
open_deals_count	int
related_open_deals_count	int
closed_deals_count	int
related_closed_deals_count	int
email_messages_count	int
people_count	int
activities_count	int
done_activities_count	int
undone_activities_count	int
reference_activities_count	int
files_count	int
notes_count	int
followers_count	int
won_deals_count	int
related_won_deals_count	int
lost_deals_count	int
related_lost_deals_count	int
active_flag	boolean
category_id	int
country_code	varchar
update_time	date
add_time	date
visible_to	int
next_activity_id	int
last_activity_id	int
address_country	varchar
cc_email	varchar

Persons

COLUMN	TYPE
id	int
company_id	int
owner_id	int
org_id	int
name	varchar
first_name	varchar
last_name	varchar
open_deals_count	int
related_open_deals_count	int
closed_deals_count	int
related_closed_deals_count	int
participant_open_deals_count	int
participant_closed_deals_count	int
email_messages_count	int
activities_count	int
done_activities_count	int
undone_activities_count	int
reference_activities_count	int
files_count	int
notes_count	int
followers_count	int
won_deals_count	int
related_won_deals_count	int
lost_deals_count	int
related_lost_deals_count	int
active_flag	boolean
phone	varchar
email	varchar
update_time	date
add_time	date
visible_to	int
next_activity_id	int
last_activity_id	int
last_incoming_mail_time	date
last_outgoing_mail_time	date
cc_email	varchar

Stages

COLUMN	TYPE
id	int
order_nr	int
name	varchar
active_flag	boolean
deal_probability	int
pipeline_id	int
rotten_flag	boolean
rotten_days	int
add_time	date
update_time	date