Holistics Docs - End-to-End Business Intelligence Platform

The Holistics Documentation

Welcome to the Holistics Documentation. You'll find comprehensive guides and documentation to help you start working with Holistics as quickly as possible, as well as support if you get stuck. Let's jump right in!

Documentation    Get Started

Import Pipedrive Data

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

ETL for Pipedrive

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

Add new data import

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.

Choose pipedrive as data source

Step 3: Select/Create Destination Table

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

Setup Destination

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.

Validate Pipedrive Sync

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.

Pipedrive Import Job

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.

Pipedrive Job History

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

Import Pipedrive Data